Senior Data EngineerUK Remote | Occasional travel to London (approximately 1&#x2013;2 times per month) Exciting opportunity for a Senior Data Engineer to join a growing technology function at an important stage of its data transformation journey. The business is developing a new group-wide data platform using Azure, with Power BI as the primary analytics and reporting layer. This is a hands-on role with genuine scope to influence how the platform is built, establishing engineering standards, patterns and best practices as the data environment continues to mature. Microsoft Fabric is also part of the platform&apos;s ongoing development, offering the opportunity to contribute to its evolution. You will take a leading role in building and extending data pipelines, working with Python, SQL and Fabric across a broad range of enterprise source systems and data domains. You&apos;ll also help shape the technical standards for the platform, ensuring data is reliable, secure, governed and accessible across the organisation. The Role:<ul><li>Build, maintain and extend data ingestion, transformation and orchestration pipelines using Python, SQL and Azure technologies.</li><li>Develop and optimise data solutions within Azure Synapse Analytics, supporting the ongoing development of the wider data platform.</li><li>Develop data models and curated datasets to support Power BI, analytics and data science.</li><li>Help establish engineering standards, reusable patterns and best practices across a growing data platform.</li><li>Work across multiple enterprise source systems and data domains, with responsibility for data quality, governance, security and platform performance.</li><li>Contribute to the ongoing development of the platform, including its adoption and use of Microsoft Fabric.</li><li>Provide technical guidance to other engineers and help develop the wider organisation&apos;s use of its data platform.</li></ul> The Person:<ul><li>Strong commercial experience as a hands-on Data Engineer, ideally having helped build or mature a cloud data platform rather than solely operating an established environment.</li><li>Strong hands-on experience with Python and SQL, alongside practical experience building data platforms using Azure Synapse Analytics and wider Azure technologies.</li><li>Experience building and maintaining production data pipelines, data models and analytics-ready datasets, ideally with Power BI as a consumption layer.</li><li>Good understanding of modern data architecture, including lakehouse and warehouse patterns, data quality, governance and security.</li><li>Experience with Microsoft Fabric would be beneficial, but the key requirement is a strong foundation in Python, Synapse and building data platforms.</li><li>Comfortable working across a complex or multi-site organisation and collaborating with architects, analysts, data scientists and wider technology teams.</li></ul> This is a fantastic opportunity to join a well-established business at a relatively early stage of its data journey, taking on a key hands-on engineering role with genuine influence over how its group-wide data platform develops. You&apos;ll have the opportunity to work with established Azure technologies while contributing to the platform&apos;s evolution, including its use of Microsoft Fabric.

Senior Data Engineer

Candidates must be legally authorized to work in the United States. <a href="https://himalayas.app/companies/lendingtree">LendingTree</a> and its affiliates (“<a href="https://himalayas.app/companies/lendingtree">LendingTree</a>”) will not provide or assume sponsorship for employment visas for this position, now or in the future.The Opportunity As a Data Engineer at <a href="https://himalayas.app/companies/lendingtree">LendingTree</a>, you’ll build the pipelines, models, and data services behind reporting, analytics, and data science across our lending and insurance businesses. You’ll tackle complex integration and modeling challenges, improve reliability and cost efficiency, and apply practical AI tools to help the team deliver better data solutions faster.<h3>How You’ll Make an Impact</h3><ul>
<li>Build and operate scalable batch and real-time streaming pipelines, ETL/ELT workflows, and database applications across multiple lines of business, with clear plans for schema changes, retries, and recovery.</li>
<li>Design dimensional models and reusable datasets for business, analytics, and data science needs. Perform complex data analysis to validate business rules, identify trends and anomalies, and uncover opportunities.</li>
<li>Own the reliability and efficiency of your data solutions: automate quality checks, monitor freshness, tune performance and compute costs, and participate in the on-call rotation to resolve incidents and prevent recurrence.</li>
<li>Create reusable frameworks and development patterns that improve delivery speed and consistency. Apply automated testing, code review, and repeatable deployments; maintain technical standards, runbooks, and learning materials.</li>
<li>Partner with business users and engineering teams to clarify requirements, resolve issues, and contribute to the data engineering roadmap, including platform capabilities, priorities, technical trade-offs, and delivery estimates.</li>
<li>Apply AI tools to development, testing, documentation, and troubleshooting. Validate generated code and results, protect sensitive data, and assess whether these tools improve quality and reduce delivery time.</li>
</ul><h3>Who You’ll Work With</h3>You’ll join the Data Engineering team, working with your manager, fellow engineers, and partners in analytics, data science, product, and business operations across Lending and Insurance. You’ll also collaborate with platform and infrastructure teams to manage dependencies, support production services, and turn business priorities into practical data solutions.<h3>What You’ll Bring</h3><ul>
<li>5+ years of hands-on experience in data engineering, including data warehousing, ETL/ELT development, and analytics, with a record of delivering and supporting production solutions.</li>
<li>Advanced SQL skills, including writing, tuning, and debugging complex queries and using data analysis to investigate problems.</li>
<li>Experience designing data lakes and warehouses on scalable, distributed platforms, with an understanding of batch and streaming integration patterns.</li>
<li>Strong dimensional modeling skills and sound data warehousing practices, including defining grain, fact and dimension tables, and how historical changes are represented.</li>
<li>Ability to deliver projects with minimal guidance in an Agile team, using testing, version control, documentation, and systematic troubleshooting to build maintainable solutions.</li>
<li>Clear written, verbal, and data presentation skills, including the ability to understand business needs and explain findings and technical decisions through documentation, presentations, or dashboards.</li>
</ul>What Will Help You Thrive You’re curious about the business behind the data, learn new tools thoughtfully, communicate issues early, and share both credit and lessons learned. Experience in any of the following is a plus:<ul>
<li>Snowflake virtual warehouses, performance and cost tuning, Streams and Tasks, and/or SQL Server.</li>
<li>Matillion, dbt, or similar tools for data integration and transformation.</li>
<li>Python, C#, or PowerShell for integration and automation; Git/GitLab for collaboration and CI/CD workflows.</li>
<li>Power BI, Tableau, or Streamlit for dashboards, data applications, and communicating insights.</li>
<li>using AI-assisted development tools such as Claude Code, Codex, Cursor, or Maia to accelerate coding, testing, documentation, and troubleshooting while validating generated code and results.</li>
<li>S. in Computer Science, Mathematics, or a related field, or equivalent practical experience.</li>
</ul><h3>What Success Looks Like</h3><ul>
<li>Production pipelines meet agreed freshness and reliability targets, with clear monitoring, ownership, and recovery procedures.</li>
<li>Business, analytics, and data science partners use tested models with consistent definitions and less manual reconciliation.</li>
<li>Query tuning and pipeline improvements produce measurable reductions in runtime, compute cost, or recurring incidents.</li>
<li>Reusable frameworks, useful documentation, and validated AI workflows shorten delivery time while maintaining quality.</li>
</ul><h3>Life at <a href="https://himalayas.app/companies/lendingtree">LendingTree</a>
</h3>We’re a collaborative, entrepreneurial team that’s curious, creative, and always ready to roll up our sleeves and get things done. You’ll work alongside smart, driven people who care about doing great work — and about helping each other succeed.We believe the best ideas come from different perspectives, and we’re committed to creating a workplace where people feel welcomed, valued, and empowered to make an impact. You’ll have the trust and flexibility to do your best work, the opportunity to take ownership and try new things, and teammates who genuinely enjoy working together.And while we work hard, we don’t take ourselves too seriously. We celebrate wins, recognize great work (our GSD — Get Stuff Done — Award is a fan favorite), and make time to have some fun along the way.Come grow with us, make an impact, and help us build what’s next.<h3>What We Offer</h3>We want you to feel supported at work and beyond. Our benefits and programs are designed to help you stay healthy, recharge, plan for the future, and bring your best to whatever matters most to you.<ul>
<li>Medical, dental, and vision insurance</li>
<li>401(k) matching</li>
<li>Generous time off</li>
<li>Wellness programs and resources</li>
<li>Annual performance bonus eligibility</li>
</ul><h3>Base Pay:</h3>The base pay range for this position is $100,000-130,000; pay offered may vary based on location, internal factors, job-related knowledge, skills, and experience.Incentive Compensation: This position is eligible for an annual performance bonus.Work Authorization: This role is not eligible for immigration sponsorship. Please do not apply for this role if you will need employer sponsorship now or in the future to begin or continue employment.<h3>Everyone Belongs Here</h3><a href="https://himalayas.app/companies/lendingtree">LendingTree</a> is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion (or creed), gender, gender expression, age, national origin, disability, marital status, sexual orientation, or military status.If you believe you need a reasonable accommodation in order to search for a job opening or to submit an application, please email us at .CCPA DisclosureOriginally posted on <a href="https://himalayas.app">Himalayas</a>

<a href="https://jobicy.com/company/discord" target="_blank" rel="noopener">Discord</a> has a highly engaged community of millions of daily active users who use the platform for many different reasons, but there’s one thing that nearly everyone does: play video games. Discord plays a uniquely important role in the future of gaming, and we are focused on making it easier and more fun for people to hang out before, during, and after playing games.
Discord seeks a seasoned Data Engineer, focusing on our advertising product data. In this role, you will drive technical vision and strategy for ads data engineering in support of our ML initiatives while building and maintaining sophisticated data pipelines, datasets, and analytical tools. You will lead cross-functional initiatives to transform our advertising products through data-driven insights and mentor fellow engineers to deliver exceptional results.
This role works heavily with Data Science, Machine Learning, and product. If leading technical innovation, architecting scalable solutions, and empowering teams through data excites you, we encourage you to make a move!
What You'll Be Doing
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<li>Design and own core ads data models: fact/dim tables, canonical datasets, and aggregation layers that power delivery, measurement, targeting, attribution, and ML use cases.</li>
<li>Build and maintain the ML data that enables ads ranking, delivery, and targeting - including feature development, label generation workflows, intra-day training, and ML input observability to catch data quality issues before they degrade model performance.</li>
<li>Build conversion measurement pipelines and integrate third-party attribution data - including Conversion Attribution and Mobile Measurement Partner (MMP) integrations (Adjust, AppsFlyer, Singular) - ensuring attribution accuracy and data parity across measurement surfaces.</li>
<li>Build batch and near real-time pipeline infrastructure across the ads ecosystem - pushing toward lower-latency data for ML and reporting use cases on our BigQuery + dbt + Dagster stack. Partnering with Data Platform on launch and success of new data processing engines to support low latency requirements..</li>
<li>Develop data quality frameworks, monitoring systems, automated anomaly detection, and SLA infrastructure for critical ads pipelines at massive scale.</li>
<li>Proactively identify foundational data infrastructure gaps - including those with broad implications across ML, measurement, and reporting - and design scalable, canonical solutions that multiple teams can depend on.</li>
<li>Build systems from scratch in a rapidly evolving, greenfield advertising data environment - making sound architectural decisions with incomplete information and balancing short-term delivery with long-term infrastructure investment.</li>
<li>Drive alignment across Data Science, ML Engineering, Ads Product, and GTM teams through clear narratives that connect data infrastructure decisions to business outcomes and revenue impact.</li>
<li>Mentor engineers through technical challenges, code and design reviews, and ownership of complex projects - contributing to the culture and engineering standards of the Data Engineering team team.</li>
</ul>
What you should have
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<li>5+ years of hands-on experience writing production code and architecting data pipelines with high-volume consumer data in advertising technology domains (ad delivery, ranking, targeting, identity, conversion measurement).</li>
<li>Deep expertise in digital advertising data engineering - specifically in ads delivery, conversion measurement, attribution pipelines, or ML feature data infrastructure. Experience with Conversion Data and APIs, MMP integrations, or identity graph infrastructure is strongly valued.</li>
<li>Demonstrated experience building data models in a greenfield or 0-to-1 environment where requirements change frequently, documentation is sparse, and architectural decisions are made with incomplete information.</li>
<li>Expert-level SQL and Python. Strong ability to design performant, maintainable data models and write production-quality pipeline code.</li>
<li>Proven hands-on experience with data quality audits, monitoring systems, and automated anomaly detection for massive-scale datasets (billions+ rows) - including quality frameworks designed for ML inputs.</li>
<li>Strong technical communication skills with the ability to drive alignment, influence prioritization, and earn adoption from technical stakeholders.</li>
<li>Collaborative mindset and strong cross-functional instincts with experience building trusted working relationships with Data Science, ML Engineering, and Product teams.</li>
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Bonus Points
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<li>Passion for Discord or gaming communities</li>
<li>Experience with data visualization and dashboarding technologies (Looker, Tableau, or similar)</li>
<li>Experience with designing data architecture to power a variety of use cases, including reporting (internal and external), adhoc analysis, experimentation.</li>
<li>Working with Data AI tools to establish greater self service utility for your customers.</li>
<li>Experience building near real-time or streaming pipeline infrastructure (e.g., Kafka, Spark Streaming, or equivalent) in addition to batch processing is preferred.</li>
</ul>
The US base salary range for this full-time position is $220,500 to $245,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits. 
Why Discord? 
Discord plays a uniquely important role in the future of gaming. We're a multiplatform, multigenerational and multiplayer platform that helps people deepen their friendships around games and shared interests, and helps developers build and grow their businesses. We believe games give us a way to have fun with our favorite people, whether listening to music together or grinding in competitive matches for diamond rank. Join us in our mission! Your future is just a click away!
Discord is committed to inclusion and providing reasonable accommodations during the interview process. We want you to feel set up for success, so if you are in need of reasonable accommodations, please let your recruiter know.
Please see our Applicant and Candidate Privacy Policy for details regarding Discord’s collection and usage of personal information relating to the application and recruitment process by clicking <a href="https://discord.com/terms/applicant-candidate-privacy-policy" rel="nofollow ugc noopener" target="_blank">HERE.</a>

Senior Data Engineer, Ads

About Our ClientThe organization operates a consumer marketplace that uses machine learning and generative AI to help millions of renters find homes. Founded in 2009, the platform features more than six million rental units and has secured approximately $169 million in funding. The company is advancing toward an AI-first strategy while modernizing the revenue, Salesforce, and data infrastructure that powers its marketplace. About the OpportunityThe Senior Data Engineer II leads the end-to-end design and management of data pipeline architecture within a focused, high-impact data platform team. This senior individual contributor role combines hands-on engineering, production operations, and independent architectural decision-making. The position helps shape how analytics engineering, data science, and product engineering teams build and operate on the data platform. Responsibilities&#x2022; Own architecture across data ingestion, transformation, modeling, and serving layers.&#x2022; Design improvements that optimize warehouse costs, compute efficiency, access control, reliability, and observability.&#x2022; Lead large cross-functional projects and multiple concurrent technical initiatives from design through delivery.&#x2022; Develop monitoring, testing, and alerting systems to improve production visibility and reliability.&#x2022; Enhance orchestration, CI/CD, data access, and developer experience across the platform.&#x2022; Mentor data and analytics engineers and provide technical guidance on architecture and data modeling decisions.&#x2022; Develop practical AI-powered tools and automation to increase engineering efficiency and team leverage.&#x2022; Troubleshoot production data infrastructure and resolve complex pipeline and platform issues.&#x2022; Communicate architectural decisions, tradeoffs, and technical recommendations to technical and non-technical stakeholders. Requirements&#x2022; 6&#x2013;9 years of experience as a data engineer or data platform engineer.&#x2022; Strong hands-on SQL and Python skills suitable for production environments.&#x2022; Production experience with containerized data infrastructure, including deployment and operational troubleshooting.&#x2022; Experience with pipeline orchestration tools such as Airflow.&#x2022; Experience with cloud data warehouses such as BigQuery.&#x2022; Proven ability to own data pipeline architecture end to end.&#x2022; Strong understanding of tradeoffs involving data freshness, cost, scalability, reliability, and system simplicity.&#x2022; Ability to communicate complex technical concepts and architectural tradeoffs effectively.&#x2022; US work authorization without current or future visa sponsorship. Pay Range and Compensation Package&#x2022; Base salary range of $145,000&#x2013;$207,000 per year.&#x2022; Competitive equity compensation. Benefits &amp; Perks&#x2022; Strong emphasis on sustainable work pace and work-life balance.&#x2022; High ownership within a small data platform team.&#x2022; Meaningful greenfield engineering opportunities.&#x2022; Fully remote work within the United States.&#x2022; Opportunity to attend company on-sites up to four times per year.&#x2022; Full-time senior individual contributor position. Equal Opportunity Statement: Our client is an equal opportunity employer. They celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, or national origin. Note: RemoteHunter is not the Employer of Record (EOR) for this role. Our purpose in this opportunity is to connect exceptional candidates with leading employers. We help job seekers worldwide discover roles that match their goals and guide them to complete their full application directly through the hiring company&#x2019;s career page or ATS.

Senior Data Engineer II

Big Data Application Developer - Remote Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential. Job Title: Big Data Application Developer Location: 100% Remote (United States) Position Type: Full-time, Direct W2 Salary Range: $100,000&#x2013;$150,000 Annually Experience: 6+ years Sponsorship:&#x202F;U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position. Job Summary We are seeking an experienced Big Data Application Developer to design, build, and operate large-scale data processing pipelines and analytics platforms on Hadoop and related big-data ecosystems. In this role you will be responsible for ingesting, transforming, and analyzing massive volumes of structured and unstructured data to support enterprise analytics, machine learning, and reporting workloads. The ideal candidate will combine deep technical expertise across the Hadoop ecosystem with strong software engineering fundamentals and a clear understanding of how to deliver reliable, performant, and cost-effective data platforms in production environments. Required Qualifications <ul><li>Bachelor&#x2019;s degree in Computer Science, Engineering, or a related technical discipline</li><li>Five or more years of professional experience designing and operating big-data pipelines on Hadoop</li><li>Strong hands-on expertise with Apache Spark (Scala, Python, or Java) in production environments</li><li>Solid experience with Hive, HDFS, Sqoop, HBase, and the broader Hadoop ecosystem</li><li>Hands-on experience with streaming data platforms such as Kafka, Spark Streaming, or Flink</li><li>Strong SQL skills and experience working with both relational and NoSQL data stores</li><li>Experience with workflow orchestration tools such as Airflow or Oozie</li><li>Solid understanding of distributed systems concepts, including partitioning, replication, and fault tolerance</li><li>Strong scripting skills in Python or Shell</li><li>Excellent troubleshooting, debugging, and documentation skills </li></ul>Preferred Qualifications <ul><li>Experience operating Hadoop on cloud platforms such as AWS EMR, Azure HDInsight, or Databricks</li><li>Familiarity with modern lakehouse formats (Delta, Iceberg, Hudi)</li><li>Exposure to data governance tooling such as Apache Atlas or Collibra</li><li>Experience with Kubernetes-based data platforms (Spark-on-K8s, Trino)</li><li>Hands-on experience with CI/CD and infrastructure-as-code in data engineering workflows </li></ul>How to Apply Would you like to know more about this opportunity? For immediate consideration, please send your resume to&#x202F;jenny@bvteck.com&#x202F;or contact us at (908) 505-3544. Learn more about Bright Vision Technologies at www.bvteck.com. Bright Vision Technologies is an Equal Opportunity Employer. Equal Employment Opportunity (EEO) Statement Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall. BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees&apos; ability to perform their job duties may result in disciplinary action up to and including termination of employment. Powered by JazzHR u7cgLX5Eiq

Big Data Application Developer

Data Engineer Location: San Francisco, California, United States Industry: Software Development Work Setting: Remote Are you passionate about building modern data platforms, creating scalable data pipelines, and enabling data-driven decision-making through reliable, secure, and intelligent data systems? We are seeking a Data Engineer to own and evolve the organization&apos;s data platform, ensuring high-quality, accessible, and well-governed data that powers analytics, business operations, and AI-driven innovation.In this role, you will be responsible for designing, building, and maintaining end-to-end data infrastructure, including data ingestion, transformation, orchestration, warehousing, governance, and automation. You will work closely with engineering, product, operations, and business teams to create scalable solutions that unlock the full value of organizational data. Key ResponsibilitiesData Platform Engineering<ul><li>Own and manage the end-to-end enterprise data platform, ensuring reliability, scalability, security, and performance.</li><li>Design and maintain data architectures that support analytics, reporting, operational workflows, and AI initiatives.</li><li>Continuously improve platform capabilities, operational efficiency, and data accessibility.</li><li>Develop scalable systems that support evolving business requirements.</li></ul>Data Pipeline Development<ul><li>Build, optimize, and maintain robust data ingestion and transformation pipelines.</li><li>Design ETL/ELT processes that move data efficiently across platforms and systems.</li><li>Ensure data pipelines are reliable, observable, and capable of handling growing data volumes.</li><li>Automate data movement and processing workflows using modern engineering practices.</li></ul>Data Warehousing &amp; Modeling<ul><li>Manage and optimize cloud data warehouse environments.</li><li>Design and maintain scalable data models that support analytics, reporting, and self-service business intelligence.</li><li>Establish data structures that improve usability, performance, and consistency.</li><li>Partner with stakeholders to define metrics, dimensions, and business reporting standards.</li></ul>Data Quality &amp; Governance<ul><li>Implement data quality frameworks, validation processes, and monitoring solutions.</li><li>Establish governance controls that ensure accuracy, consistency, and trust in organizational data.</li><li>Manage data access controls, permissions, and compliance requirements.</li><li>Support data stewardship and governance initiatives across the organization.</li></ul>Orchestration &amp; Automation<ul><li>Develop and maintain orchestration frameworks that automate data workflows and dependencies.</li><li>Ensure efficient scheduling, monitoring, and recovery mechanisms for data processes.</li><li>Build operational tooling that improves visibility and platform observability.</li><li>Enhance platform reliability through automation and engineering best practices.</li></ul>AI &amp; Intelligent Data Solutions<ul><li>Support the integration of AI and machine learning capabilities within the data ecosystem.</li><li>Explore opportunities to automate workflows and enhance operations using AI-driven solutions.</li><li>Collaborate on initiatives that leverage enterprise data to power intelligent applications.</li><li>Contribute to innovative approaches that improve data accessibility and decision-making.</li></ul>Infrastructure &amp; DevOps<ul><li>Implement Infrastructure-as-Code and modern deployment practices.</li><li>Support cloud-native architectures, containerized environments, and scalable infrastructure solutions.</li><li>Establish CI/CD pipelines and deployment automation for data platforms.</li><li>Collaborate with platform and infrastructure teams to ensure operational excellence.</li></ul>Cross-Functional Collaboration<ul><li>Partner with engineering, product, analytics, operations, and business teams to understand data needs.</li><li>Translate business requirements into scalable technical solutions.</li><li>Provide technical guidance on data architecture, governance, and platform strategy.</li><li>Support organization-wide initiatives that rely on trusted and accessible data.</li></ul> Required Qualifications<ul><li>5+ years of experience building and maintaining production-grade data platforms.</li><li>Strong expertise in:</li><li>Snowflake</li><li>dbt</li><li>SQL</li><li>Python</li><li>Experience designing and maintaining modern data pipelines and data architectures.</li><li>Strong understanding of data modeling principles and best practices.</li><li>Experience with workflow orchestration tools such as:</li><li>Airflow</li><li>Dagster</li><li>Similar orchestration platforms</li><li>Experience implementing data governance and access management controls.</li><li>Strong analytical and problem-solving skills.</li><li>Excellent communication and stakeholder collaboration abilities.</li></ul> Key Technical Skills<ul><li>Snowflake</li><li>dbt</li><li>SQL</li><li>Python</li><li>ETL / ELT Development</li><li>Data Pipelines</li><li>Data Modeling</li><li>Data Governance</li><li>Data Warehousing</li><li>Data Quality Management</li><li>Airflow</li><li>Dagster</li><li>AWS</li><li>Terraform</li><li>Kubernetes</li><li>CI/CD</li><li>Infrastructure as Code</li><li>Workflow Automation</li><li>Data Architecture</li><li>Analytics Engineering</li></ul> Preferred Qualifications<ul><li>Experience supporting AI, machine learning, or intelligent automation initiatives.</li><li>Hands-on experience building cloud-native data platforms.</li><li>Experience implementing data observability and monitoring frameworks.</li><li>Knowledge of modern analytics engineering practices.</li><li>Experience supporting enterprise-scale governance and security initiatives.</li><li>Background working within fast-growing technology-focused organizations.</li></ul>

Data Engineer

Please note: Our Talent team at <a href="https://jobicy.com/company/jobber" target="_blank" rel="noopener">Jobber</a> will be offline for Jobber Impact - our flagship event of the year, bringing Jobberinos together to connect, learn, and celebrate what we're building - starting October 6th and extending until October 9th. We’ll be back to go through applications and reach out with an update on your candidacy once we return next week!
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This will be updated automatically on all job posts above our What you can expect from Jobber headline.
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The automated email to candidates will have the same message as above.
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<h3>Does working with Data motivate and excite you? Do you want to make a difference cross functionally? </h3>
Then Jobber might be the place for you! We’re looking for a new Staff Data Engineer to join our Data Platform Team.
Jobber exists to help people in small businesses be successful. We work with small home service businesses, like your local plumbers, painters, and landscapers, to transform the way service is delivered through technology. With Jobber they can quote, schedule, invoice, and collect payments from their customers, while providing an easy and professional customer experience. Running a small business today isn’t like it used to be—the way we consume and deliver service is changing rapidly, technology is evolving, and customers expect more. That’s why we put the power and flexibility in their hands to run their businesses how, where, and when they want!
Our culture of transparency, inclusivity, collaboration, and innovation has been recognized by Great Place to Work, Canada’s Most Admired Corporate Cultures, and more. Jobber has also been named on the Globe and Mail’s Canada’s Top Growing Companies list, and Deloitte Canada’s Technology Fast 50™, Enterprise Fast 15, and Technology Fast 500™ lists. With an Executive team that has over thirty years of industry experience of leading the way, we’ve come a long way from our first customer in 2011—but we’ve just scratched the surface of what we want to accomplish<a href="https://www.youtube.com/watch?v=EkfZmHrRLx4&amp;list=PLoktA_D-2UEnxMLfCe93bANKXVXd2bdN8&amp;index=24" rel="nofollow ugc noopener" target="_blank"> for our customers</a>.
We help employees grow professionally; we have a ton of onboarding resources, tutorials, hackathons and buddies to support learnings and provide opportunities to innovate. We have a range of experience levels on teams which allows for mentor/mentee opportunities. Leaders at Jobber work with empathy and support employees to build healthy work-life harmony. Bring your dedication and passion to this job to fulfill your goals.
The team:
The Data Integration team's mission is to empower teams across Jobber with the right data, at the right time, in the right place, so they can deliver business value better and faster. Key responsibilities include: data ingestion and Change Data Capture (CDC), including materializing CDC streams into tables in Snowflake; data activation (egress); managing the systems involved in the movement and transformation of data; self-serve tooling; and data integrity and governance.
The role:
As a Staff Data Engineer, you will play a critical role in shaping the future of data integration at Jobber. As a technical champion and force multiplier, you’ll lead and mentor a team of exceptional data engineers while solving complex technical challenges. Your expertise will span architecture, technical leadership, design, and hands-on coding, enabling you to significantly influence the direction of data at Jobber.
Beyond day-to-day delivery, you will dedicate time to work acceleration, cross-team initiatives, exploration of emerging technologies, addressing technical debt, and investing in the future of engineering at Jobber. This is a highly strategic and hands-on position where you’ll combine deep technical expertise with leadership to design resilient systems, empower teams across the organization to self-serve with confidence, and ensure our data remains a trusted asset that accelerates business growth.
As a Staff Data Engineer, you will:
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Shape Foundational Data Components: Design, build, and maintain scalable batch and real-time data pipelines, while also looking across systems and ahead to anticipate future needs.
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Demonstrate Technical Mastery: Deliver high-quality solutions through deep expertise in modern data tools and technologies. Champion technical excellence within the team by setting best practices, raising the bar for engineering quality, and mentoring team members at all levels to support their growth and career development.
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Drive Reliability &amp; Resilience: Establish testing and reliability standards, SLAs (uptime, RTO, RPO), and disaster recovery playbooks. Lead major reliability initiatives to minimize downtime and protect critical business data.
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Advance Observability &amp; Governance: Build frameworks for monitoring, logging, lineage, and auditing to ensure visibility, compliance, and trust in data. Define governance policies that enforce data integrity, availability, and reliability across the platform.
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Accelerate and Empower Data Access: Develop self-service tools, frameworks, and automation that reduce manual effort, improve efficiency, and enable teams across engineering, analytics, and data science to work effectively with data while minimizing dependency on the Data Platform team.
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Contribute to Strategic Planning: Partner with Technical Program Managers to define and refine strategic roadmaps, ensuring that data engineering priorities align with business objectives.
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Drive Cross-Team Collaboration: Collaborate with Staff Engineers and technical leaders across domains to identify friction points, and work collectively to design solutions that improve system reliability, consistency, and scalability.
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Accelerate Business Growth: Work closely with data analysts, scientists, and product teams to enable fast, seamless exploration, analysis, modeling, and reporting. Build automation and infrastructure that reduce friction and accelerate decision-making.
</li>
<li>
Safeguard Data Integrity: Own the integrity and reliability of data, ensuring stakeholders across the organization maintain trust in the insights and decisions driven by it.
</li>
<li>
On-Call Rotation: Members of the Data Platform team participate in an on-call rotation, covering one week at a time. When an incident occurs outside of regular working hours, we provide time off in lieu to support healthy balance and recovery. From time to time, major maintenance work may require team members to serve as primary or secondary on-call support over a weekend. Jobber is committed to maintaining a fair, transparent, and humane on-call experience. Your interview team will be happy to walk you through how we manage on-call responsibilities in practice.
</li>
</ul>
To be successful, you should have:
<ul>
<li>
Core Data Engineering Expertise: Hands-on experience with batch and real-time data processing frameworks, lakehouse/warehouse management, large-scale data transformation, data serialization, workflow orchestration and dimensional modeling (star/snow-flake schemas)
</li>
<li>
Scalable Systems Development: Proven ability to design and deliver highly scalable, maintainable, and high-performance solutions across multiple layers of the technology stack, leveraging containerization, CI/CD, and API development.
</li>
<li>
AWS Cloud Proficiency: Strong understanding of AWS services relevant to the data domain, with hands-on experience leveraging them to design and implement data solutions.
</li>
<li>
Technical Leadership &amp; Engineering Excellence: Demonstrated success guiding teams through complex, high-impact projects while providing architectural direction and serving as a trusted technical lead. Exceptional proficiency in software design, system architecture, and coding, with a focus on long-term maintainability, performance, and resilience.
</li>
<li>
Reliability &amp; DevOps Practices: Strong background in infrastructure-as-code (Terraform, CloudFormation), observability (logging, monitoring, tracing), and system reliability.
</li>
<li>
Collaboration &amp; Adaptability: Exceptional communication skills, self-motivation, and resourcefulness, with the ability to navigate ambiguity, prioritize effectively, and deliver results in fast-paced environments.
</li>
</ul>
It would be really great (but not a deal-breaker) if you had:
<ul>
<li>
Machine Learning Platform Experience: Exposure to ML platforms and distributed compute frameworks (e.g., Ray, TensorFlow, PyTorch). Experience collaborating with Data Scientists to operationalize models, implement drift detection, or scale ML workloads.
</li>
<li>
Cross-Domain Engineering Experience: Hands-on exposure to non–data engineering codebases, such as web application frameworks (Ruby on Rails) and modern front-end stacks (TypeScript/React).
</li>
<li>
API &amp; Integration Knowledge: Familiarity with GraphQL, API layer design, and performance optimization.
</li>
<li>
Platform Building Experience: Prior work on developer tooling or shared platforms that supported multiple engineering domains.
</li>
<li>
Governance &amp; Compliance Awareness: Knowledge of data privacy, security, and compliance in cloud-based data environments.
</li>
<li>
Knowledge of data privacy, security, and compliance considerations in a cloud-based data environment.
</li>
</ul>
Compensation:
At Jobber, we also believe that compensation should be transparent, fair, and supportive of your experience and growth. This role has a minimum annual salary of $169,200 CAD, a midpoint of $199,100 CAD and a maximum salary of $228,900 CAD, designed to reflect the progression from learning the ropes to truly excelling.
We design our compensation to reflect each new hire's skills, experience, and the complexity of the role, ensuring a fair and competitive salary. Our range is intentionally broad to support growth and long-term impact, with fully established hires typically starting around the midpoint. The higher end of the range is reserved for those who have demonstrated deep expertise and lasting contributions, while offers below the midpoint reflect strong potential with room to develop. This approach ensures that compensation aligns with both an individual's current capabilities and their opportunity for future growth.
Base salary is just one part of a total compensation package that will include equity rewards, annual stipends for health and wellness, retirement savings matching, and an extended health package with fully paid premiums for body and mind. Your professional growth matters to us too! You'll have access to a dedicated talent development program that includes career coaching and opportunities for career development.
We believe in transparency and open conversations about compensation. If you have any questions about our approach, we're happy to discuss them throughout the hiring process!

What you can expect from Jobber:
<ul>
<li>
A total compensation package that includes an extended health benefits package with fully paid premiums for both body and mind, matching in RRSP, TFSA or FHSA, and stock options.
</li>
<li>
A dedicated Talent Development team and access to coaching, learning, and leadership programs to help you grow your career, reach your goals, and unlock your full potential.
</li>
<li>
A unique opportunity to build, grow, and leave your impact on a $400-billion industry that has no dominant player...yet.
</li>
<li>
To work with a group of people who are humble, supportive, and give a sh*t about our customers.
</li>
</ul>
We believe that diverse teams perform better and that fostering an inclusive work environment is a key part of growing a successful team. We welcome people of diverse backgrounds, experiences, and perspectives. We are an equal opportunity employer, and we are committed to working with applicants requesting accommodation at any stage of the hiring process.

A bit more about us:
Job by job, we’re transforming the way service is delivered. Your lawn care provider, home cleaning service, plumber or painter could use Jobber to better connect with their customers, save time in the office, invoice faster, and get paid! We’re bringing tens of thousands of people together with technology to deliver billions of dollars a year in services to happy customers. Jobber exists to help make these small businesses successful, and when they’re successful we all win!

Staff Data Engineer

About the roleJoin a team of CRM specialists and analysts who keep Amnesty International Australia&#x2019;s CRM systems and data processes running smoothly and reliably. This is a 12 month contract covering core CRM administration and data processing while the team delivers a major systems project. We need someone who can get up to speed quickly and manage the day-to-day workload independently, with minimal oversight. There&#x2019;s also scope to spot and fix minor process inefficiencies along the way. The details<ul><li>Fixed-term contract, 12 months</li><li>75 hours per fortnight</li><li>Level 7.1</li><li>Remote work</li><li>Reports to the Data, Insights and Supporter Care (DISC) Manager</li><li>Start date: as soon as possible</li></ul> What you&#x2019;ll do<ul><li>Configure and maintain our CRM systems, including user roles, permissions and security settings</li><li>Manage data imports, exports and integrations with external platforms</li><li>Provide help desk support for colleagues, including queries, segments and troubleshooting</li><li>Maintain relationships with vendors, including Blackbaud and payment processors, and manage escalations</li><li>Support data quality, master data management, and privacy and security compliance</li><li>Assist Finance with payment authorisations and transaction processing</li><li>Flag clunky or overly manual processes and fix the quick wins</li><li>Document processes clearly so knowledge isn&#x2019;t held by one person</li><li>Train colleagues and stakeholders on CRM functionality and data processes</li></ul> What you&#x2019;ll bringEssential:<ul><li>Significant experience administering CRM platforms in a fundraising, membership or similar environment</li><li>A proven ability to run CRM administration independently, with minimal supervision or ramp-up time</li><li>Experience with data imports, exports and integrations between systems</li><li>Strong Excel skills and confidence working with data</li><li>The ability to provide effective user support and training</li></ul> Highly desirable:<ul><li>Experience with Blackbaud CRM and BVDL (Brightvine Data Link), or similar enterprise fundraising platforms</li><li>Experience with payment processing systems and reconciliation</li><li>Familiarity with data governance principles</li><li>A track record of identifying and implementing process improvements</li></ul> What makes you a great fitYou&#x2019;re reliable and self-directed, and you&#x2019;re happy to own the day-to-day without close supervision. You&#x2019;d rather fix a problem than write about it, and you&#x2019;re comfortable saying &#x201C;this process doesn&#x2019;t make sense&#x201D; and suggesting a better way. You can explain technical matters to non-technical colleagues and document things so others can follow them. What success looks like in your first six months<ul><li>You&#x2019;ve taken full ownership of day-to-day CRM administration</li><li>Data processing, imports, exports and help desk support are running smoothly with no backlog</li><li>Key processes are documented, so knowledge no longer depends on a single person</li><li>You&#x2019;ve built strong working relationships with all teams</li></ul>

Database Specialist

<div class="content-intro">
<h3>About Us</h3>
<a href="https://himalayas.app/companies/ujet">UJET</a> leads the way in AI-powered contact center innovation, delivering a future-proof, cloud platform that redefines the customer experience with cutting-edge AI, true multimodality, and a mobile-first approach. We infuse AI across every aspect of your customer journey and contact center operations, to drive automation and efficiency. <a href="https://himalayas.app/companies/ujet">UJET</a>'s AI solutions empower agents, optimize customer journeys, and transform contact center operations for elevated experiences and actionable insights. Built on a cloud-native architecture with a unique CRM-first approach, <a href="https://himalayas.app/companies/ujet">UJET</a> ensures unmatched security, scalability, and prioritized data insights (without storing PII). Designed for effortless use, <a href="https://himalayas.app/companies/ujet">UJET</a> partners with businesses to deliver exceptional interactions, smarter decision-making, and accelerated growth in the AI-driven world.
Learn more at .
</div><h3>Opportunity</h3><a href="https://himalayas.app/companies/ujet">UJET</a> is looking for a Data Engineer to join our growing Data Platform team. You'll own our data systems end to end: CDC replication out of production MySQL, the pipelines and jobs that shape data in BigQuery, the Terraform-managed infrastructure underneath, and the Looker models on top. dbt is central to how we work. You'll build models yourself and set the patterns that let analysts, product partners, and engineers ship their own safely. You should be comfortable debugging a replication issue in the morning and tuning a Looker explore in the afternoon.This data powers reporting for thousands of customer tenants, including embedded Looker analytics for enterprise customers, and the internal metrics our Operations and Finance teams run the business on. Over the coming year, our focus is data trust and reliability, platform modernization, and treating data as a product. You'll help shape all three.<h3>Our Stack</h3><ul>
<li>
Sources and ingestion: Cloud SQL (MySQL) and BigQuery via GCP Datastream (CDC)</li>
<li>
Warehouse and transformation: BigQuery, dbt (dbt Labs)</li>
<li>
Orchestration: GKE-based, using Kubernetes CronJobs and Argo Workflows</li>
<li>
Semantic layer and reporting: Looker / LookML </li>
<li>
Languages: Python and SQL; core application infra is Ruby on Rails and Go</li>
</ul><h3>What You'll Do</h3><h3>Data platform enablement</h3><ul>
<li>Build and evolve the data platform foundations that make it easy and safe for others to ship dbt work (project structure, environments, permissions, patterns, documentation)</li>
<li>Establish and maintain standards and guardrails for dbt development (testing strategy, source freshness, documentation, code review practices)</li>
<li>Improve the developer experience for data workflows, including CI/CD, automated checks, and repeatable deployment patterns</li>
<li>Manage data infrastructure as code with Terraform, including pipelines, IAM, and environments</li>
</ul><h3>Ingestion and CDC</h3><ul>
<li>Improve and troubleshoot CDC replication from MySQL to BigQuery with Datastream</li>
<li>Build tooling for backfills, drift detection, and reconciliation between source databases and the warehouse</li>
<li>Contribute to infrastructure decisions on data ingestion and platform evolution, including latency, throughput, and alternative CDC approaches</li>
</ul><h3>Trusted metrics and analytics</h3><ul>
<li>Partner with Analytics and Finance to define and deliver trusted metrics and dashboards in Looker</li>
<li>Build and maintain analytics-ready datasets that support self-serve reporting and experimentation</li>
<li>Support customer-facing, multi-tenant reporting with a focus on correctness, tenant isolation, and query performance</li>
</ul><h3>Data modeling and transformation (dbt + BigQuery)</h3><ul>
<li>Develop and optimize BigQuery data models for analytics and product use cases</li>
<li>Implement ELT best practices in dbt, including testing, documentation, and versioning</li>
</ul><h3>Pipelines, reliability, and cost</h3><ul>
<li>Design, build, and maintain scalable data pipelines using Python, dbt, and containerized jobs on GKE</li>
<li>Ensure data quality, reliability, and observability for critical datasets and reporting</li>
<li>Optimize performance and cost across BigQuery and data pipelines</li>
</ul><h3>Cross-functional delivery</h3><ul>
<li>Integrate data workflows with backend services and APIs</li>
<li>Work with Product and Engineering to translate business needs into data solutions</li>
</ul><h3>Requirements</h3><ul>
<li>5+ years of software engineering experience, with deep data platform experience</li>
<li>Strong programming skills in Python</li>
<li>Strong SQL skills and experience with analytical data modeling</li>
<li>Hands-on experience with BigQuery (or a similar cloud data warehouse)</li>
<li>Production experience with dbt (dbt Labs), including building models yourself</li>
<li>Experience building or improving the infrastructure around data workflows (reliability, observability, CI/CD, permissions, environments, deployment patterns)</li>
<li>Experience with infrastructure as code, preferably Terraform</li>
<li>Experience with a major cloud platform (GCP preferred)</li>
<li>Strong software engineering fundamentals (testing, version control, code reviews)</li>
</ul><h3>Preferred Qualifications</h3><ul>
<li>Experience with GCP services (Datastream, Cloud Storage, Cloud Run, and Pub/Sub)</li>
<li>Change data capture experience (GCP Datastream or MySQL binlog/GTID replication)</li>
<li>Experience with Kubernetes-based orchestration (Argo Workflows or similar)</li>
<li>Experience with Looker (LookML, semantic modeling, dashboards)</li>
<li>Familiarity with Ruby on Rails or Go, which power the application-layer services our data platform depends on</li>
<li>Experience collaborating with Product to gather requirements and translate business needs into data solutions</li>
</ul><h3>Compensation</h3>Annual US Hiring Range: $140,000 – $160,000**A candidate's actual placement within this range will depend on geographic location, work experience, education, and/or skill level.<div class="content-conclusion">
<h3>Why <a href="https://himalayas.app/companies/ujet">UJET</a>?</h3>
<ul>
<li>
Impactful Work: Be at the forefront of innovation, directly shaping the future of customer experience. </li>
<li>
Dynamic Culture: Join a collaborative, inclusive team that values big ideas, creative solutions, and powerful relationships.</li>
<li>
Comprehensive Benefits: Medical, dental, vision, 401(k) plan, wellness benefits, and more.</li>
</ul>
<h3>
<a href="https://himalayas.app/companies/ujet">UJET</a> is an Equal Opportunity Employer</h3>
<a href="https://himalayas.app/companies/ujet">UJET</a> provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
<h3>Compliance Responsibilities</h3>
Security, data protection and compliance (SDPC) are paramount to the success of our partnerships. All roles at <a href="https://himalayas.app/companies/ujet">UJET</a> require compliance with legal and regulatory requirements and acceptance and adherence to all policies and standards within <a href="https://himalayas.app/companies/ujet">UJET</a>. Personnel acknowledges they are personally responsible for reporting any suspected violations or abuse and are required to complete SDPC training and fulfill role-specific SDPC responsibilities.
<h3>AI Use in Our Hiring Process</h3>
<a href="https://himalayas.app/companies/ujet">UJET</a> uses artificial intelligence (AI) technology to assist with the initial review and filtering of job applications against the qualifications listed in this posting. AI does not make hiring decisions, does not conduct interviews, and has no authority to reject or advance a candidate on its own. All application review decisions, candidate screening, and interviews are conducted by members of our human recruiting and hiring teams.
<h3>Reasonable Accommodation</h3>
If you would like to request a reasonable accommodation as part of the application process, including an alternative to AI-assisted screening, please contact .
<h3>Work Authorization &amp; Sponsorship</h3>
Applicants must be legally authorized to work in the country in which this position is located, without the need for current or future employer-sponsored visa sponsorship. <a href="https://himalayas.app/companies/ujet">UJET</a> does not sponsor employment visas for this role.
</div>Originally posted on <a href="https://himalayas.app">Himalayas</a>

Location : This is a remote role, offering the flexibility to work virtually from anywhere within the UK. Contract Type : Permanent The Opportunity Reporting directly to the Head of Customer Management Platforms and working under the day-to-day technical leadership and direction of the Principal Engineer, this role is responsible for enabling secure, reliable and scalable movement of data between customer management platforms, enterprise systems and analytical platforms. The role supports the technical delivery, operation and continuous improvement of integration capabilities across the Customer Management Platforms estate, ensuring consistent engineering standards, architectural alignment and operational excellence. What You Will Be Doing Integration Engineering &amp; Data Management <ul><li>Design, build and support integrations across Customer Management Platforms and enterprise applications.</li><li>Develop API, event-driven and batch integration solutions using Informatica CDI/CAI and approved architectural patterns.</li><li>Support data movement, transformation and synchronisation across Salesforce, Treasure Data, Informatica Customer 360, Snowflake, SAP and related platforms.</li><li>Implement reusable integration standards and ensure data flows are reliable, scalable and secure.</li><li>Support onboarding of new data sources and downstream consumers. </li></ul>Platform Operations &amp; Support <ul><li>Monitor and support production integration services and data pipelines.</li><li>Implement proactive monitoring, alerting and operational dashboards.</li><li>Troubleshoot integration issues, perform root cause analysis and support incident and problem management activities. </li></ul>Technical &amp; Engineering Excellence <ul><li>Collaborate with the Principal Engineer to align with platform architecture, technical standards and engineering best practices.</li><li>Contribute to technical design, platform roadmaps and continuous improvement initiatives.</li><li>Maintain technical documentation, testing, automation and CI/CD practices.</li><li>Ensure compliance with security, audit and data governance requirements. </li></ul>What You&#x2019;ll Bring <ul><li>Advanced SQL expertise with 5+ years&apos; experience in Data Engineering or Integration Engineering.</li><li>Strong hands-on experience with Informatica Cloud Data Integration (CDI), Cloud Application Integration (CAI) and ETL/ELT development.</li><li>Proven experience designing, building and supporting enterprise data integrations.</li><li>Experience integrating cloud platforms, enterprise applications and data services.</li><li>Snowflake data engineering experience.</li><li>REST API development and integration experience.</li><li>Strong understanding of event-driven integration and system-to-system connectivity.</li><li> Data modelling and data quality principles. </li><li> CI/CD, DevOps, monitoring, observability and operational support practices. </li><li> Agile delivery experience. </li><li> Strong analytical, problem-solving and stakeholder management skills. </li><li> Experience working across multiple teams, suppliers and technology platforms. </li><li> Understanding of data privacy, security and compliance requirements. </li></ul>Additional Desirable Skills <ul><li>Salesforce ecosystem (Sales Cloud, Service Cloud, Revenue Cloud, CPQ)</li><li>Customer Data Platforms (Treasure Data) and Customer Engagement Platforms</li><li>Informatica Customer 360, Business 360 and Data Quality</li><li>MuleSoft, SAP and Databricks</li><li>Master Data Management (MDM) and Pricing Solutions (Pricefx) </li></ul>We Are RS At RS, we are making amazing happen for a better world. As a global product and service solutions provider, we help industrial customers operate more efficiently and sustainably. Operating in 33 markets, we support around one million customers worldwide with more than 875,000 stocked products, access to over five million additional products, and a range of service solutions designed to help businesses thrive. What sets us apart is our people. More than 8,500 colleagues around the world bring technical expertise, digital innovation, and a customer first mindset to everything we do. Guided by our values &#x2013; we are one team, we deliver brilliantly, we do the right thing, and we make every day better, we&apos;re creating an environment where our people can grow, contribute and make a meaningful impact. Join us and help make amazing happen. Rewards Our Reward Strategy Philosophy is designed to offer market competitive base salaries and provide all of our people the opportunity to participate in a short-term incentive, enabling them to share in the success of the Company. Our total reward package is more than just the cash; our recognition and benefit offering provide the opportunity for us to recognise, reward and enable the wellbeing of our people at all stages of their journey with RS. Our rewards and benefits vary by country, but include: <ul><li>Financial - pension/retirement; life assurance; salary finance (payroll deduction loan scheme) </li><li>Wellbeing - medical plans; health screening; critical illness; disability insurance; holiday / paid time off; employee assistance programme; discounted gym/health club membership </li><li>Lifestyle - transportation assistance schemes (e.g., cycle to work, travel loans, car leasing); onsite catering/lunch vouchers; retail discounts </li><li>Spotlight &#x2013; our global recognition programme provides a platform to highlight and recognise people role modelling our values </li></ul>Ready to Make Amazing Happen? Join over 8,500 colleagues and help us shape the future of our industry. Whoever you are, wherever you are &#x2014; it all starts here. Apply now and make RS a part of your journey.

Developer - CDI

About Us At Benepass we&apos;re making benefits easy. We believe people are the most important asset to any company. Traditional one-size-fits-all benefits packages no longer cut it in today&apos;s hybrid and remote-first environment. With Benepass, companies can tailor their benefits to the unique needs of their workforce. Through our easy-to-use and highly customizable fintech platform, People teams can implement, administer, and track the benefits that meet employees where they are. Employers design their benefits and perks plan by setting a contribution amount and eligible spend categories. Every employee has their own individual definition of wellness and needs different things to help them be their most productive, fulfilled self. Our Mission Helping companies reimagine how companies take care of their people. Our Investors We are backed by leading investors, including Centana Growth Partners, Portage Ventures, Threshold Ventures, Gradient Ventures, Workday Ventures, and Clocktower Technology Ventures. To date, the company has raised approximately $75 million in equity capital. Articles <ul><li>Founder Story - Jaclyn Chen</li><li>Benepass Raises $40M Series B </li></ul>Candidate Resources <ul><li>Benepass | Candidate Resource Page</li><li>Benepass Listed on Inc. Magazine&apos;s Best Workplaces of 2023 </li></ul>TEAM &amp; ROLE Benepass is hiring a Senior Data Engineer to build and scale the data platform that powers analytics, product reporting, and operational intelligence across the company. You will work on a small, high-impact data team that owns the warehouse, pipelines, transformation layer, semantic layer, and the infrastructure that makes data accessible, trustworthy, and fast. This is a hands-on senior IC role. You will own the architecture and implementation of data systems from the current 0&#x2192;1 foundation to 1&#x2192;N scale. You will partner with Product, Engineering, Customer Operations, GTM, and Finance to understand data needs, then design and build the pipelines, models, and platform capabilities that support those needs. You will take ownership of data quality, performance, cost, and the developer experience of everyone who works with data at Benepass. Your work enables data scientists, analysts, operators, and product teams to move fast with confidence. When this role is working, data is available when teams need it, queries run fast and stay cheap, definitions are clear and versioned, and the platform scales cleanly as the business grows. This is a force-multiplier role. You will build shared infrastructure, not one-off reports. You will balance short-term delivery with long-term architectural integrity. You will bring strong opinions on tooling, patterns, and quality, while staying pragmatic about build-vs-buy trade-offs and speed to value. YOU WILL Build and Scale the Data Platform <ul><li>Own the design and implementation of Benepass&apos;s data platform: warehouse (Redshift Serverless), replication (Airbyte/DMS), orchestration, transformation (dbt), and semantic layer (Cube).</li><li>Architect data pipelines that reliably replicate production data (Aurora/RDS, application databases) into the warehouse with correct handling of PII, multi-tenancy, and data residency constraints.</li><li>Maintain and evolve orchestration and job scheduling infrastructure so pipelines run reliably, recover gracefully from failures, and surface clear observability when things break.</li><li>Design the platform for performance and cost: query patterns, materialization strategies, incremental models, partitioning, and warehouse scaling/tuning.</li><li>Make pragmatic build-vs-buy decisions; favor leverage and speed over custom solutions where mature tooling exists. </li></ul>Own Data Quality, Governance, and Correctness <ul><li>Build data quality checks, automated testing, and validation into every pipeline and model so bad data gets caught before it reaches stakeholders.</li><li>Define and enforce patterns for data grain, slowly changing dimensions, multi-tenant access controls, and row-level security so financial and benefits data stays correct under scrutiny.</li><li>Work with Engineering on source data contracts, instrumentation gaps, and schema evolution so upstream changes don&apos;t break downstream reporting.</li><li>Maintain clear lineage, documentation, and metadata so people know where data comes from, what it means, and when it was last refreshed.</li><li>Partner with Security and Compliance on data residency, encryption, access controls, and audit requirements for regulated data. </li></ul>Enable Self-Service Analytics and Product Reporting <ul><li>Design and build dbt models (staging through marts) that codify business logic, dimensional models, and metrics in version-controlled SQL.</li><li>Author and maintain Cube models and measures so governed metrics serve cleanly into BI tools (Metabase, Looker, etc.), product reporting surfaces, and internal dashboards.</li><li>Implement row-level security patterns in Cube so multi-tenant data stays isolated and access controls reflect the business model.</li><li>Optimize for query speed: pre-aggregations, caching strategies, and materialized views that let stakeholders query large datasets interactively.</li><li>Provide clear paths for analysts and data scientists to extend models, write safe queries, and build new reports without waiting for engineering. </li></ul>Partner Across The Company To Deliver Data Solutions Product &amp; Engineering <ul><li>Work with Product to understand data needs for internal tools, customer-facing reporting, and product analytics.</li><li>Partner with Engineering (Core Services, Client Apps, Platform) to instrument events, define schemas, and close gaps where product data doesn&apos;t land cleanly in the warehouse.</li><li>Collaborate on production pipelines that power product features: reporting surfaces, usage dashboards, and data-driven workflows. </li></ul>Customer Operations, GTM, and Finance <ul><li>Support Customer Operations with data for implementation health, claims/CX metrics, utilization, and operational quality.</li><li>Provide GTM/Sales with pipeline, conversion, and retention data that joins Salesforce with product usage and warehouse data.</li><li>Work with Finance on revenue, margin, billing, and financial reporting requirements; ensure financial data is reconcilable and audit-ready. </li></ul>Data Scientists and Analysts <ul><li>Build the foundation analysts and data scientists depend on: clean staging models, dimensional marts, and governed metrics.</li><li>Provide documentation, training, and support so engineers and analysts can extend models and write queries safely.</li><li>Collaborate on complex analyses where data engineering work unlocks science or speeds decision-making. </li></ul>Drive Platform Reliability, Performance, And Developer Experience <ul><li>Own the end-to-end reliability of data pipelines: monitoring, alerting, incident response, and post-mortems when things break.</li><li>Improve query performance and cost: identify slow queries, optimize models, tune warehouse configuration, and right-size resources.</li><li>Build tooling and automation that reduces toil: deployment workflows, testing frameworks, data refresh triggers, and observability.</li><li>Maintain clear documentation, runbooks, and onboarding materials so the platform is accessible to new team members and partners.</li><li>Introduce new tools and patterns when they compound platform leverage; balance experimentation with production stability. </li></ul>Shape the Data Platform Roadmap <ul><li>Identify architectural gaps, technical debt, and scaling bottlenecks; propose solutions with clear trade-offs and sequencing.</li><li>Lead the evaluation and adoption of new platform capabilities: real-time data, streaming pipelines, CDC patterns, data catalogs, or next-generation BI/semantic layers.</li><li>Advocate for platform investments that multiply team impact: better observability, faster development cycles, cleaner abstractions, and lower operational overhead.</li><li>Partner with the Platform lead to align data infrastructure with broader AWS/Kubernetes/infra patterns and security posture. </li></ul>About You A Senior Data Platform Builder <ul><li>You&apos;ve built data platforms from the ground up or scaled them through significant growth.</li><li>You write production-quality SQL and Python; you&apos;re fluent in modern data stacks (warehouse, orchestration, transformation, BI/semantic layers).</li><li>You have strong opinions on data modeling, testing, and quality, with pragmatism about when to cut scope and ship.</li><li>You design systems for correctness first, then performance, then cost; you care deeply about data integrity in regulated domains.</li><li>You ship incremental value while keeping long-term architecture coherent. </li></ul>A Technical Leader and Force Multiplier <ul><li>You operate at a senior IC level (P4): you take ownership of ambiguous problems and drive them to durable solutions.</li><li>You partner across Product, Engineering, Customer Operations, GTM, and Finance without needing a formal PM or project manager.</li><li>You mentor data scientists, analysts, and engineers; you raise the bar for how the company thinks about data.</li><li>You make build-vs-buy decisions that favor leverage and team velocity.</li><li>You communicate technical trade-offs clearly to non-technical stakeholders and advocate for platform investments that compound. </li></ul>Requirements <ul><li>5+ years of data engineering experience, with growing ownership of platform architecture, data pipelines, and data quality.</li><li>Strong SQL and Python; experience building production data pipelines on modern data stacks.</li><li>Hands-on experience with data warehouses (Redshift, Snowflake, BigQuery) and transformation frameworks (dbt).</li><li>Experience building and maintaining data replication pipelines (CDC, DMS, Airbyte, Fivetran, or similar).</li><li>Solid understanding of dimensional modeling, data grain, slowly changing dimensions, and data quality patterns.</li><li>Experience with semantic layers or metrics platforms (Cube, LookML, MetricFlow) and how they serve governed metrics into BI tools.</li><li>Comfort with AWS data services (RDS, S3, Redshift, DMS, Lambda) and infrastructure-as-code (Terraform preferred).</li><li>Experience working with PII, multi-tenant data, row-level security, and compliance requirements in regulated domains (fintech, healthcare, benefits).</li><li>Clear written and verbal communication; you can explain technical decisions to stakeholders across the company.</li><li>Fit with a high-ownership, high-trust culture. We hire for skill and for how people work with others. </li></ul>Nice to have <ul><li>Experience with orchestration tools (Airflow, Dagster, Prefect, Mage).</li><li>Real-time data, streaming pipelines, or CDC patterns (Kafka, Kinesis, Debezium).</li><li>BI tools (Metabase, Looker, Omni, Superset, Tableau).</li><li>Data observability and cataloging tools (Monte Carlo, Great Expectations, Atlan).</li><li>Fintech, payments, benefits, or healthcare domains where data correctness and compliance are critical.</li><li>Experience with Kubernetes, Docker, or containerized data workloads.</li><li>Exposure to data science workflows: feature engineering, experimentation platforms, or ML pipelines. </li></ul>OUR TECHNOLOGY AND STACK AWS (Aurora/RDS, DMS, Redshift Serverless, S3, Lambda), dbt, Cube, Airbyte, Python, SQL, Metabase, Terraform, Docker, Kubernetes. Most of your build time will be in SQL, Python, dbt, and data infrastructure on AWS. ROLE LOCATION &amp; TRAVEL You will be expected to attend company-wide on-site events three times per year. Compensation <ul><li>Base Salary $175,000 to 195,000 + equity </li></ul>Range(s) is subject to change. Benepass takes a number of factors into account when determining individual starting pay, including market comparables, interview performance, peer compensation, and years of experience. What We Offer <ul><li>95% coverage of medical, dental, and vision</li><li>Fantastic benefits (of course &#x1F603;), including:</li><ul><li>$250 WFH setup (one time)</li><li>$500/year Learning &amp; Development Benefit</li><li>$150/month cell phone + internet</li><li>$100/month Wellness</li><li>$100/month Co-working and Commuter Benefit</li></ul><li>We offer several team onsites a year</li><li>Flexible PTO </li></ul>At Benepass, we are working towards reimagining how companies take care of their people. We are committed to creating an inclusive environment for all our employees and are seeking to build a team that reflects the diversity of the people we hope to serve with our revolutionary products. Benepass is proud to be an equal-opportunity employer.

Sr. Data Engineer

AFL manufactures industry-leading fiber optic cable, connectivity and accessories and provides engineering and installation services for some of the largest telecom customers in the world. Our company was founded in 1984 with a single fiber optic cable and today, we manufacture thousands of products, generate an excess of $4B in revenue, and employ approximately 12,000 associates worldwide. At AFL, we recognize that our employees are our greatest asset. We hire and train each individual, investing in them to ensure success in their careers. With a commitment to professional development and growth, let us connect you to your next career opportunity. What We Offer <ul><li>Flexible time off policy </li><li>401K Company match (up to 4% - dollar for dollar)</li><li>Professional development, training, and tuition reimbursement programs</li><li>Excellent medical, dental, vision, and life insurance policy options</li><li>Opportunities for career advancement with an industry leading company! </li></ul>We are seeking an experienced ETL Developer to design, develop, maintain, and optimize enterprise data integration solutions. The ideal candidate will be responsible for extracting data from multiple source systems, transforming data according to business requirements, and loading it into data warehouse. This role requires strong SQL skills, expertise in data warehousing concepts, and experience with modern data integration and orchestration tools. This position will be able to work remotely from anywhere in the United States. Key Responsibilities Data Integration &amp; Development <ul><li>Design, develop, and maintain ETL/ELT processes to support enterprise reporting and analytics.</li><li>Develop source-to-stage and stage-to-data warehouse data pipelines.</li><li>Create and maintain data transformation logic, mappings, and business rules.</li><li>Develop and optimize database views, stored procedures, and SQL scripts.</li><li>Integrate data from databases, APIs, file systems, and third-party applications.</li><li>Implement error handling, logging, monitoring, and recovery processes within ETL workflows. </li></ul>Data Warehouse &amp; Data Management <ul><li>Support enterprise data warehouse architecture and data modeling initiatives.</li><li>Ensure data quality, consistency, and integrity throughout the data lifecycle.</li><li>Perform data validation, reconciliation, and root cause analysis.</li><li>Collaborate with business analysts and stakeholders to translate requirements into technical solutions.</li><li>Document data flows, mappings, technical specifications, and operational procedures. </li></ul>Orchestration &amp; Automation <ul><li>Develop and maintain workflow scheduling and orchestration processes.</li><li>Configure job dependencies, alerts, notifications, and automated recovery procedures.</li><li>Monitor ETL jobs and proactively identify performance bottlenecks.</li><li>Support production deployments and post-deployment validation activities. </li></ul>Support &amp; Continuous Improvement <ul><li>Troubleshoot ETL failures and data quality issues.</li><li>Participate in code reviews and adherence to development standards.</li><li>Recommend improvements to data integration processes and system performance.</li><li>Support production incidents and perform impact analysis as needed. </li></ul>Required Qualifications <ul><li>3+ years of experience developing ETL/ELT solutions.</li><li>Strong experience with SQL and relational database platforms.</li><li>Experience with data warehouse concepts, dimensional modeling, and data integration.</li><li>Experience with ETL tools such as Azure Data Factory &amp; Fabric.</li><li>Strong analytical and problem-solving skills.</li><li>Experience working with APIs, flat files, XML, JSON, and other data formats. </li></ul>Preferred Qualifications <ul><li>Knowledge of data lake and lakehouse architectures.</li><li>Experience with workflow scheduling tools such as Redwood RunMyJobs or equivalent.</li><li>Experience with Service Now.</li><li>Familiarity with Power BI and enterprise reporting platforms.</li><li>Familiarity with Linux.</li><li>Experience with Change Data Capture (CDC) and real-time data integration.</li><li>Understanding of DevOps, CI/CD, and source control tools.</li></ul>

ETL Developer (Azure Data Factory/MS Fabric) - Remote Opportunity

Prominence Advisors is actively seeking a Data Engineer (Snowflake) to join our team. Who We Are Prominence is a healthcare and life sciences technology and consulting firm dedicated to helping leading organizations do more with their data. With deep expertise across the full ecosystem &#x2014; spanning providers, payers, and life sciences &#x2014; we turn complex data into actionable insight. We deliver a full spectrum of services, including advisory, analytics, optimization, and IT staffing. Our work helps organizations operate more efficiently, improve patient outcomes, and deliver measurable financial impact through smarter use of data. Recognized as a 2x Best in KLAS organization, we partner with more than 120 health systems and 40 life sciences organizations, including 7 of the top 10 U.S. News &amp; World Report-ranked institutions. Through our life sciences brands, Tegra Analytics and WLH Consulting &amp; Learning Solutions, we extend these capabilities to pharmaceutical and biotech organizations &#x2014; combining data, consulting, and learning to advance commercial excellence. By connecting strategy, data, and execution, we help organizations translate data into clarity, strategy into action, and vision into measurable results. At our core, we are a people-first, values-driven organization that believes strong teams and trusted partnerships are what ultimately make healthcare and life sciences smarter. Your Role Our consultants guide our customers through complex data challenges to summit the task at hand. As a Data Engineer, you will design, build, and maintain pipelines and workflows that enable our customers to put their data to work. You will need to be able to create order out of chaos, transforming raw sources into clean, reliable, and scalable data streams. Our ideal team members are humble, smart, and driven to ensure our customer&apos;s success. This includes a passion to deliver high-quality results, while teaching our counterparts how to fish and grow the skills needed to support and expand upon the deliverables of our projects. If this sounds like you, and you meet the requirements below, we encourage you to apply. If you know of someone else who would be a great fit, let us know. Requirements Prominence is looking for a Data Engineer with deep Snowflake experience and strong SQL and Python skills to help us build and optimize data pipelines in partnership with some of the nation&apos;s leading healthcare providers. Our ideal candidate has built and operated production workloads on Snowflake &#x2014; not just queried them &#x2014; and understands how warehouse sizing, data modeling, and pipeline design translate directly into performance and cost. You should be able to build scalable data pipelines that ingest, transform, and deliver data from diverse sources (EHRs, claims, APIs, CRM) into analytics-ready structures in Snowflake. You should also be well versed in DevOps practices, integrating pipeline development with version control and CI/CD to support repeatable deployments across environments, change tracking, and appropriate approval gates. You&apos;ll work directly with client architects and analysts, so you should be comfortable explaining tradeoffs as well as implementing them. More important than any single tool is the demonstrated desire and ability to tackle new and unfamiliar technical challenges. This position is a full-time, salaried role with benefits. There is no relocation required. Candidates are required to have a suitable home office to operate from. Minimum Qualifications <ul><li>3+ years of professional experience in data engineering or related roles</li><li>2+ years of hands-on Snowflake experience in a production environment, including:</li><ul><li>Strong Snowflake development experience, including query profile analysis, query optimization, and debugging</li><li>Virtual warehouse sizing, scaling policies, and credit/cost management</li><li>Data loading and ingestion patterns (COPY INTO, Snowpipe, external stages, external tables)</li><li>Table design and performance features (clustering keys, micro-partition behavior, materialized views, Time Travel, zero-copy cloning)</li><li>Snowflake security model: roles, grants, and RBAC hierarchy design</li></ul><li>Proficiency in Python (or another programming/scripting language such as Scala or Java)</li><li>Experience building transformation and orchestration logic in Snowflake using one or more of the following:</li><ul><li>dbt</li><li>Snowflake Streams and Tasks, or Dynamic Tables</li><li>Snowpark (Python)</li><li>Apache Airflow, Azure Data Factory, or another orchestration framework</li></ul><li>Solid grounding in ETL/ELT principles, dimensional and data-vault-style modeling, and data warehousing concepts</li><li>Experience with at least one major cloud provider (AWS, Azure, or GCP), including storage and networking basics as they relate to Snowflake integrations </li></ul>Desired Qualifications <ul><li>Healthcare industry knowledge and experience (Epic Clarity/Caboodle, HL7, FHIR, claims data)</li><li>Experience handling PHI in Snowflake: dynamic data masking, row access policies, tagging, and HIPAA-aligned account configuration</li><li>SnowPro certification (SnowPro Core, or SnowPro Advanced: Data Engineer)</li><li>Experience with CI/CD pipelines, Git, and DevOps workflows, including schema migration tooling (schemachange, Flyway, Liquibase, or dbt-native deployment)</li><li>Familiarity with Infrastructure-as-Code, particularly the Snowflake Terraform provider</li><li>Experience with Snowflake Secure Data Sharing, the Snowflake Marketplace, or reader accounts</li><li>Familiarity with Snowflake Cortex AI functions, Streamlit in Snowflake, or Iceberg tables</li><li>Experience with real-time/streaming ingestion into Snowflake (Kafka connector, Snowpipe Streaming, Kinesis, Pub/Sub)</li><li>Experience migrating workloads to Snowflake from legacy platforms (SQL Server, Teradata, Oracle, Netezza, Redshift)</li><li>Exposure to other cloud data platforms (Databricks, BigQuery, Redshift) and the ability to speak to how they compare </li></ul>Success Criteria Successful team members at Prominence display the following: <ul><li>High degree of professionalism; treats others with respect, keeps commitments, builds trust within a team, works with integrity, and upholds organizational values</li><li>Highly organized; able to manage multi-faceted work streams</li><li>Self-motivated; able to manage schedules, meet deadlines, and monitor your personal work product</li><li>Highly adaptable; able to acclimate quickly to new project assignments and work environments</li><li>Creative; not paralyzed by problems and able to work collaboratively to find novel solutions</li><li>Clear communication skills; ability to convey messaging in clear and concise written and verbal communications</li><li>Ability to anticipate issues before they arise and escalate effectively</li><li>Passion to mentor and guide others </li></ul>Benefits Prominence is dedicated to hiring the best and brightest minds in healthcare, and maintaining a culture that rewards our employees for following their passion. You&apos;ll join a team of highly motivated and passionate people who do great work for the nation&apos;s leading healthcare organizations, including 7 of the top 10 academic medical centers. In the past 5 years, we&apos;ve received 20+ Best Places to Work Awards and are highly rated in KLAS, reflecting the quality work from our team of A-players who move mountains daily for our customers. We strive to create the best working environment with the best team, so that we can continue to drive innovation in healthcare faster. <ul><li>Our 2 nodes of business: Analytics and Epic Services - offer you a diversified career path, stability in a rapidly changing market, and opportunities for growth within Prominence</li><li>Prominence is a fully remote company, with no requirements on where you live or work within the US and flexibility to manage your schedule</li><li>We offer 15 days PTO and up to 16 paid Holidays each year for full-time staff</li><li>We offer a diverse healthcare offering, including low and high deductible health plans, HSAs, LTD/STD Insurance, Health and Dependent Savings Accounts, Vision, Dental, 401k offering, an annual Professional Development fund, and Signing Bonuses</li></ul>

Data Engineer (Snowflake)

About The Company Versant (Nasdaq: VSNT) is a pioneering media and entertainment company renowned for its influential brands that shape culture, inform audiences, and foster lasting connections. Operating across four core markets&#x2014;political news and opinion, business news and personal finance, golf, and sports and genre entertainment&#x2014;Versant delivers high-quality content through a diverse portfolio of iconic brands including CNBC, MS NOW, USA Network, Golf Channel, Oxygen, E!, SYFY, and its sports division USA Sports. The company also manages a suite of digital assets such as Fandango, Rotten Tomatoes, GolfNow, and GolfPass, providing comprehensive entertainment and information services to a global audience. With a focus on innovation and excellence, Versant remains committed to delivering impactful content and building strong community engagement in the evolving media landscape. About The Role We are seeking a highly skilled Data Engineer II to join our dynamic team. In this role, you will be instrumental in building, maintaining, and enhancing our data platforms and pipelines that underpin GolfNow and the broader Sports Next ecosystem. Your expertise will support the development of reliable, scalable data solutions that facilitate analytics, reporting, and product innovation. Operating at the intersection of sports and technology, you will collaborate closely with data engineers, software engineers, product teams, and analytics partners to translate complex business and technical requirements into effective data architectures. You will take ownership of assigned data engineering initiatives, contribute to technical design discussions, and continuously strive to improve the quality, performance, and reliability of our data ecosystem. This position offers an exciting opportunity to work remotely while making a significant impact on data-driven decision-making within a leading entertainment organization. Qualifications <ul><li>Experience in data engineering or a related technical discipline with hands-on development of data pipelines in cloud environments</li><li>Strong proficiency in SQL and Python, including ETL/ELT workflows and handling structured and semi-structured data</li><li>Knowledge of data modeling, data warehousing, and modern data engineering practices</li><li>Experience with AWS technologies such as Glue, Lambda, and Step Functions or similar cloud data services</li><li>Familiarity with orchestration tools like Airflow and infrastructure-as-code tools such as Terraform</li><li>Ability to troubleshoot data and pipeline issues, identify root causes, and implement reliable solutions</li><li>Excellent collaboration and communication skills, capable of working effectively with cross-functional teams</li><li>Ability to independently manage tasks while collaborating on complex technical decisions </li></ul>Responsibilities <ul><li>Design, develop, test, and maintain scalable data pipelines and integrations across AWS and Microsoft technologies</li><li>Enhance data models and warehouse structures to support analytics, reporting, and business intelligence needs</li><li>Monitor data workflows, troubleshoot issues, and implement solutions to improve data quality, reliability, and performance</li><li>Collaborate with engineering, product, and analytics teams to understand requirements and translate them into technical solutions</li><li>Contribute to data quality, governance, testing, documentation, and operational standards throughout the data lifecycle</li><li>Participate in technical design discussions and evaluate tools, frameworks, and engineering best practices to optimize data solutions </li></ul>Benefits <ul><li>Competitive compensation package</li><li>Comprehensive health, dental, and vision insurance plans</li><li>Retirement savings options and financial planning resources</li><li>Paid time off and holiday leave</li><li>Fully remote work environment with opportunities for in-person collaboration (~10%)</li><li>Professional development and continuous learning opportunities</li><li>Inclusive and collaborative company culture </li></ul>Equal Opportunity Versant is an equal opportunity employer committed to diversity and inclusion. We do not discriminate based on race, color, religion, gender, gender identity or expression, age, national origin, disability, sexual orientation, marital status, pregnancy, veteran status, membership in the military or any other protected status under applicable law. We promote a workplace where all employees are valued and empowered to contribute to our success. Applicants requiring accommodations during the recruitment process are encouraged to contact us.

Data Engineer II

Role overview The Data Engineer builds the pipelines and data platforms that support analytics, reporting, AI development, and operational decisions. Working across ingestion, transformation, storage, modeling, and delivery, this position turns complex business needs into reliable production systems, including batch and real-time pipelines, OLTP and OLAP stores, semantic models, and BI-ready datasets. The work combines cloud engineering, automation, observability, and infrastructure-as-code in a regulated environment. Building and Operating the Data Foundation <ul><li>Design, develop, and maintain data pipelines connecting internal systems, third-party platforms, files, APIs, event streams, and databases. Build scalable ETL and ELT workflows for batch and real-time processing.</li><li>Make pipelines testable, observable, reliable, and extensible. Develop reusable integration patterns for increasing data volumes, new sources, and consumers across analytics, applications, and AI.</li><li>Design and manage architectures for transactional, analytical, and reporting workloads. Optimize data models, warehouse schemas, and curated datasets for analytics and business intelligence.</li><li>Help design and operate warehouses, lakehouses, streaming systems, and orchestration frameworks, with practical approaches to storage, partitioning, performance, retention, and lifecycle management.</li><li>Deploy and operate data pipelines and stores on AWS, GCP, or Azure. Use infrastructure-as-code, CI/CD, and automation to improve deployment consistency, speed, and reliability.</li><li>Monitor production systems through logging, alerting, and observability tools; identify and resolve issues while supporting secure, resilient, cost-conscious cloud infrastructure.</li><li>Implement data-quality checks, validation, reconciliation, and monitoring. Maintain lineage, documentation, metadata, schema-evolution standards, and operational runbooks.</li><li>Improve data accessibility, consistency, and usability with appropriate controls. Support security, privacy, auditability, and regulatory compliance.</li><li>Partner with Product, Engineering, AI, Analytics, business stakeholders, and domain subject matter experts to understand workflows and constraints and translate requirements into maintainable data solutions.</li><li>Support analysts, researchers, product teams, and operational users. Explain data availability, quality, tradeoffs, and delivery timelines to technical and nontechnical stakeholders.</li><li>Improve performance, reliability, scalability, and developer productivity; simplify architecture, reduce operational toil, and extend the value of shared data platforms.</li><li>Move iteratively from problem definition to implementation and improvement, strengthening engineering quality through design, testing, documentation, and operational discipline.</li></ul> Required Technical Background <ul><li>2&#x2013;4+ years building and operating production-grade data pipelines and systems.</li><li>Strong experience with standard ETL/ELT, orchestration, warehousing, streaming, and BI tools and platforms.</li><li>Experience with OLTP and OLAP systems and an understanding of transactional versus analytical workload tradeoffs.</li><li>Experience integrating databases, APIs, files, message queues, SaaS platforms, and event streams through flexible pipelines supporting batch and real-time processing.</li><li>Experience deploying and operating cloud data infrastructure on AWS, GCP, or Azure.</li><li>Strong SQL capabilities, including data modeling, transformation frameworks, and performance optimization.</li><li>Experience building LLM-based AI capabilities, including orchestration, evaluation, and data integration patterns.</li><li>Experience with data-engineering programming languages such as Python, Java, Scala, or Go.</li><li>Comfort with CI/CD, infrastructure-as-code, observability, and production operations.</li><li>Sound judgment when requirements are ambiguous or changing, balancing speed, reliability, and flexibility; clear communication with technical and nontechnical colleagues.</li></ul> Preferred Experience <ul><li>Orchestration and transformation platforms such as Airflow, Dagster, or dbt.</li><li>Cloud warehouses or lakehouses such as Snowflake, BigQuery, Redshift, or Databricks.</li><li>Streaming and real-time platforms such as Kafka, Kinesis, or SQS.</li><li>Curated datasets, semantic layers, and self-service analytics using Looker, Power BI, Tableau, or similar reporting tools.</li><li>Fintech, mortgage, lending, payments, insurance, or other regulated-domain experience.</li><li>Data platforms supporting AI, machine learning, or decisioning workflows.</li><li>Improving data quality, reliability, cost efficiency, and scalability as platforms grow.</li></ul> Prior fintech or finance experience is not required. Candidates with strong data-engineering skills, technical judgment, and systems thinking are encouraged to apply even if their background does not match every listed qualification. Work and Compensation This is a regular full-time, fully remote position. The posting lists New York, New York, United States, and Toronto, Canada. The salary range is USD $140,000&#x2013;$190,000, plus an annual bonus. Compensation may vary with experience, location, and other job-related factors.Benefits include medical coverage beginning on the first day and a company-matched 401(k).Employment decisions are based on merit, competence, and qualifications, without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, or any other status protected by applicable federal, state, or local law.

Data Engineer - Remote

Job Title: Data Engineer Who we are: -At CitiusTech, we constantly strive to solve the industry&apos;s greatest challenges with technology, creativity, and agility. With over 8,500 healthcare technology professionals worldwide, CitiusTech powers healthcare digital innovation, business transformation, and industry-wide convergence for over 140 organizations through next-generation technologies, solutions, and products. We aim to accelerate the transition to a human-first, sustainable, and digital healthcare ecosystem with the world&apos;s leading Healthcare and life sciences organizations and our partners.Here is an opportunity for you to make a difference and collaborate with global leaders to shape the future of healthcare and positively impact human lives. Our vision: -To inspire new possibilities for the health ecosystem with technology and human ingenuity. Responsibilities: -Analytical Data Modelling:<ul><li>Expert in data modelling.</li><li>Must be able to transform raw, fragmented data from MongoDB and PostgreSQL into clean, performant tables optimized for end user reporting</li></ul>Primary Stack:<ul><li>Expert-level SQL and Python; deep experience with Snowflake, dbt, Mongo, Postgres and Snowflake</li></ul>Data Environments:<ul><li>Proven ability to integrate and model data from both MongoDB and PostgreSQL sources.</li></ul>Governance &amp; Security:<ul><li>Proficiency in handling sensitive data under GDPR/SOC2 compliance, with a strong understanding of MDM and data lineage.</li></ul>AI &amp; Innovation:<ul><li>Ability to incorporate AI/LLM tools into the development lifecycle to drive efficiency and optimize system performance</li></ul>Experience: -<ul><li>10+ Years</li></ul>Location: -<ul><li>Remote</li></ul>Educational Qualifications: -<ul><li>Engineering Degree &#x2013; BE/ME/BTech/MTech/BSc/MSc.</li><li>Technical certification in multiple technologies is desirable.</li></ul> Life at CitiusTechWe focus on building highly motivated engineering teams and thought leaders with an entrepreneurial mindset, centered on our core values of Passion, Respect, Openness, Unity, and Depth (PROUD) of knowledge. Our success lies in creating a fun, transparent, non-hierarchical, diverse work culture that focuses on continuous learning and work-life balance.Rated by our employees as the &#x2018;Great Place to Work for&#x2019; according to the Great Place to Work survey. We offer you a comprehensive set of benefits to ensure that you have a long and rewarding career with us.Our EVPBe You Be Awesome is our EVP and it reflects our continuing efforts to create CitiusTech as a great place to work where our employees can thrive, both personally and professionally. It encompasses the unique benefits and opportunities we offer to support your growth, well-being, and success throughout your journey with us and beyond. Together with our clients, we are solving some of the greatest healthcare challenges and positively impacting human lives. Welcome to the world of Faster Growth, Higher Learning, and Stronger Impact.Join CitiusTech. Be You. Be Awesome.

We are seeking a Data Engineer with experience in projects emphasizing complex data solutions. This person will be responsible for supporting the continued performance, reliability, and availability of two critical applications, which are essential to our clients supply chain and planning operations. This Data Engineer will help support Databricks activities that minimize disruptions, maintain stable daily operations, and deliver approved fixes or enhancements as required. The Data Engineer will assist with requirements analysis, design/develop process flow, and unit/integration testing, to deliver complex data products.<ul><li>Work with the various technology teams and operational stakeholders to support and enhance two applications</li><li>Lead the Queue Management System to ensure timely processing, issue resolution, and continuity of business operations within the applications.</li><li>Design and develop database objects, tables, stored procedures, views, etc.</li><li>Design and develop ETL Processes that will transform a variety of raw data, flat files, xl spreadsheets into SQL Databases</li><li>Understands the concept of Data Marts and Data lakes and experience with migrating legacy systems to data marts/lake</li><li>Uses additional cloud technologies (e.g., understands concept of Cloud services like Azure SQL server)</li><li>Maintain comprehensive project documentation</li></ul>&#xB7; Aptitude to learn new technologies and the ability to perform continuous research, analysis, and process improvement.&#xB7; Strong interpersonal and communication skills to be able to work in a team environment to include customer and contractor technical, end users, and management team members.<ul><li>Manage multiple projects, responsibilities and competing priorities.</li></ul>Experience Needed:<ul><li>Programming languages, frameworks, and file formats such as: Python, SQL, PLSQL, DBT</li><li>Database platforms such as: Oracle, SQL Server, MySQL</li><li>Big data concepts and technologies such as Synapse &amp; Databricks</li><li>AWS and Azure cloud computing</li></ul>

Data Engineer - Databricks - REMOTE

Location: United StatesWorkplace: RemoteEmployment Type: Full-time, Permanent, ExemptExperience: 5+ years of data engineering experience building and operating production data pipelines and platforms Core Areas: Data Platform Engineering, Spark, Kafka, Iceberg, Airflow/MWAA, Data Lake Architecture, Data Governance, Data Quality Compensation: $186,500&#x2013;$255,000 per year plus bonus eligibility and equity About the Role This opportunity is for a Staff Data Engineer to take ownership of major Data Platform Engineering initiatives spanning the data lake, production pipelines, event instrumentation, data quality, data governance, and cloud data infrastructure. The role designs and operates scalable batch, streaming, and real-time data systems while helping evolve ingestion, processing, storage, and serving patterns across the platform. The position works extensively with Spark, Kafka, Iceberg, Airflow/MWAA, Druid, and EMR on EKS, with a strong focus on reliability, observability, governance, and privacy. Responsibilities also include GDPR and CCPA data controls, AI-assisted development workflows, production troubleshooting, technical leadership, and mentoring engineers. What You&apos;ll Do <ul><li>Design data solutions for batch, streaming, and real-time workloads.</li><li>Design and build reliable production data pipelines using Spark, Kafka, Iceberg, and Airflow/MWAA.</li><li>Advance data lake and data platform architecture across ingestion, processing, storage, and serving patterns.</li><li>Build, maintain, and scale cloud data infrastructure using Kafka, Airflow, Druid, and EMR on EKS with reliability and observability as core design requirements.</li><li>Implement and continuously improve data quality, observability, reliability, and governance across production data pipelines and systems.</li><li>Define and improve event instrumentation and governance standards, including event schemas, validation, and schema evolution.</li><li>Build centralized platform capabilities for PII handling, data retention, deletion, and residency to support GDPR and CCPA requirements.</li><li>Develop agent harness capabilities that encode data engineering standards, pipeline patterns, and quality gates into AI tools so agents can safely generate, review, and operate on data platform code.</li><li>Contribute hands-on to complex technical initiatives and troubleshoot production data platform issues.</li><li>Mentor engineers and collaborate with Analytics Engineering and other technical teams on complex data and platform challenges.</li><li>Embed data engineering standards, pipeline patterns, and quality gates into AI-assisted development workflows.</li></ul> Qualifications Required Experience <ul><li>5+ years of data engineering experience building and operating production data pipelines and data platforms.</li><li>Strong experience with Spark and distributed data processing, including designing and optimizing production data pipelines.</li><li>Experience designing batch, real-time, and streaming data solutions using technologies such as Kafka, Spark Structured Streaming, and change data capture (CDC).</li><li>Experience implementing data quality, observability, and reliability practices across production data systems.</li><li>Experience with cloud data infrastructure, CI/CD, and infrastructure-as-code.</li><li>Demonstrated experience leading complex data engineering initiatives end to end, from technical design and decomposition through implementation and production.</li></ul> Required Skills <ul><li>Strong programming and SQL skills with the ability to build reliable, maintainable production data systems.</li><li>Ability to navigate ambiguous technical problems, evaluate architectural tradeoffs, and make pragmatic engineering decisions.</li><li>Ability to design beyond individual pipelines and consider the full data ecosystem from upstream data producers through downstream consumers.</li><li>Experience with data governance and privacy practices, including PII management, retention, deletion, data residency, GDPR, or CCPA.</li><li>Experience with event instrumentation and governance, including event schemas, validation, and schema evolution.</li><li>Ability to collaborate with engineers on complex technical problems and establish practical engineering best practices.</li><li>Experience applying AI and emerging technologies in development workflows and helping technical teams adopt new tools through shared practices and learnings.</li></ul> Education <ul><li>BA/BS degree or equivalent professional experience.</li></ul> Benefits <ul><li>Equity through restricted stock units (RSUs).</li><li>Comprehensive medical, dental, and vision coverage for full-time employees and their dependents, with most premiums covered.</li><li>12 weeks of paid parental leave for all parents, plus 6 or more additional weeks of paid leave for birthing parents.</li><li>Inclusive support for family planning, menopause, and midlife transitions.</li><li>Flexible vacation, paid holidays, and a sabbatical program.</li><li>Mental health resources, therapy, and coaching.</li><li>401(k) with a 100% employer match of up to $6,000 per year in the United States.</li><li>Monthly localized stipends supporting work and wellness expenses, including Wi-Fi and fitness.</li><li>Eligibility for an annual company bonus program for full-time, permanent, non-commission employees.</li></ul>

Data Engineer (Remote)

Who we are... Latitude is a growing Service-Disabled Veteran Owned (SDVOSB) Company within the Federal Sector. We have experience in working with various federal clients across multiple different agencies. We believe in adopting and growing a remote work-from-home culture wherever possible to ensure a healthy work-to-life balance. We believe in automating the mundane and investing in our employees helping them grow their careers over time. We strive for innovation and want to develop solutions that we can take pride in and help break through some of the barriers that exist in technology and the government sectors today. Description... We are hiring a Data Engineer to build and run the data pipelines behind analytics and machine learning work on Google Cloud Platform for a federal health customer. You will work with data architects, data scientists, ML engineers, and application teams to ingest, transform, and deliver curated datasets in BigQuery. The role sits on a cloud operations and migration team and includes technical leadership on data engineering standards and practices. This position is fully remote in the United States. What You Will Do... <ul><li>Build, maintain, and optimize batch and streaming data pipelines on Google Cloud that support analytics and machine learning</li><li>Ingest data from APIs, databases, SaaS systems, streaming feeds, and files, then transform it and deliver curated datasets in BigQuery</li><li>Build data quality rules, schema validation, and automated tests into pipelines, and monitor pipeline health with Cloud Monitoring and Cloud Logging</li><li>Apply governance and security standards, including IAM, encryption, data masking, and auditing, and maintain pipeline infrastructure with Terraform and CI/CD</li><li>Provide technical direction on data engineering standards, lead code reviews, and document datasets, transformations, and operating procedures </li></ul>Minimum Qualifications... <ul><li>Bachelor&apos;s degree in computer science, software engineering, information systems, data engineering, or a related technical field</li><li>3+ years of hands-on data engineering experience, including building production data pipelines on a cloud platform</li><li>3+ years leading technical teams, including setting technical standards and processes for cloud and on-premises environments and guiding technology decisions</li><li>Hands-on experience with BigQuery, Cloud Storage, Dataflow, Dataproc, and Pub/Sub</li><li>Strong SQL and Python, with experience in distributed data processing and data modeling</li><li>Experience transforming large datasets and delivering ML-ready datasets for model training</li><li>Ability to obtain and maintain a federal background investigation (Public Trust) </li></ul>Preferred Qualifications... <ul><li>Master&apos;s degree in a technical discipline</li><li>Experience supporting federal government programs, especially federal health</li><li>Knowledge of regulated environments: FedRAMP, HIPAA, NIST 800-53, CIS benchmarks</li><li>Experience with Vertex AI or other ML platforms, and with feature store concepts</li><li>Experience with Cloud Composer (Airflow), dbt, Dataplex, and Datastream for change data capture</li><li>Experience with Apache Kafka or other streaming technologies, and with Looker or Looker Studio</li><li>Security certification such as CISSP or CCSP </li></ul>Clearance... <ul><li>Applicants selected will be subject to a Security Investigation and May need to Meet Requirements for Access to Protected and/or Classified Information </li></ul>Citizenship... <ul><li>Applicants need to be a US Citizen to be considered for the position and have physically resided in the United States for a minimum of 3 years due to background investigation requirements </li></ul>Employee Benefits... <ul><li>Medical, Vision, Dental</li><li>Paid Vacation &amp; Sick Time</li><li>Paid Federal Holidays</li><li>401k Retirement Plan with 100% Company Matching</li><li>Employer Paid Life Insurance</li><li>Continued Education Assistance</li><li>Employee Assistance Program (EAP)</li><li>Commuter Benefits Program</li><li>Health Savings Account (HSA) </li></ul>We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. The posted range is base annual salary, placement within the range depends on qualifications, relevant experience, and contract requirements.

Job Description: Lead GCP Data Engineer/Looker Hire: (Full-Time)Location: Remote (USA) Job SummaryWe are seeking a highly skilled and motivated Lead GCP Data Engineer to join our team on a full-time basis. In this role, you will lead the design, development, and optimization of scalable data platforms, robust data pipelines, and advanced analytical solutions on the Google Cloud Platform (GCP). You will collaborate closely with business stakeholders, data analysts, and engineering teams to translate analytical requirements into impactful, scalable data solutions. Key Responsibilities<ul><li>Design, develop, and maintain scalable data pipelines on Google Cloud Platform (GCP).</li><li>Build and optimize enterprise data solutions using BigQuery, Cloud Storage, Dataflow, Dataproc, Cloud Composer, and Pub/Sub.</li><li>Develop and maintain semantic data models using LookML in Looker.</li><li>Create reusable dashboards, reports, and analytics solutions to support critical business decision-making.</li><li>Lead data architecture discussions and provide technical guidance and best practices to engineering teams.</li><li>Implement data governance, data quality standards, security policies, and performance optimization best practices.</li><li>Collaborate directly with business stakeholders to translate complex analytical requirements into scalable data architectures.</li><li>Mentor junior engineers, foster engineering excellence, and conduct rigorous code reviews.</li><li>Troubleshoot and resolve data pipeline, reporting, and performance bottlenecks.</li><li>Work closely with DevOps and cloud infrastructure teams to implement seamless CI/CD pipelines and infrastructure as code practices.</li></ul> Required Skills &amp; Expertise1. GCP Data EngineeringStrong, hands-on enterprise experience with:<ul><li>BigQuery</li><li>Cloud Composer (Airflow)</li><li>Dataflow</li><li>Dataproc</li><li>Cloud Storage</li><li>Pub/Sub</li><li>Cloud Functions</li><li>IAM &amp; Security best practices</li></ul>2. Looker / LookML<ul><li>Advanced experience in Looker development and administration.</li><li>Expertise in LookML modeling, explores, views, dimensions, measures, and derived tables.</li><li>Experience designing, scaling, and maintaining enterprise semantic layers.</li><li>Strong understanding of dashboard development, caching strategies, and performance tuning.</li></ul>3. Data Engineering Fundamentals<ul><li>Advanced SQL writing and complex query optimization skills.</li><li>Extensive experience with ETL/ELT frameworks.</li><li>Deep data warehousing and dimensional modeling (Star/Snowflake schemas) expertise.</li><li>Hands-on experience with both batch and real-time data processing workflows.</li></ul>4. Programming Languages<ul><li>Python</li><li>SQL</li><li>Shell Scripting</li></ul>Preferred Skills<ul><li>Experience with dbt (data build tool).</li><li>Working knowledge of Terraform and Infrastructure as Code (IaC).</li><li>Experience with CI/CD tools such as GitHub Actions, GitLab CI, or Jenkins.</li><li>Exposure to machine learning workloads and MLOps on GCP.</li><li>Familiarity with Agile/Scrum delivery methodologies.</li></ul>Qualifications<ul><li>Employment Type: Full-Time</li><li>Bachelor&#x2019;s or Master&#x2019;s degree in Computer Science, Information Technology, or a related technical field.</li><li>Google Cloud Certifications:</li><li>Professional Data Engineer (Required)</li><li>Professional Cloud Architect (Preferred)</li></ul>Nice-to-Have<ul><li>Domain experience in Retail, Financial Services, Healthcare, or E-commerce.</li><li>Proven migration experience moving legacy on-premise systems or other cloud platforms (AWS/Azure) to GCP.</li><li>Strong stakeholder management and client-facing communication skills.</li></ul>

Lead GCP Data Engineer

Where you&#x2019;ll add valueThis role is a full-time, 12month maximum term contract and sits within the Financial Crime Maturity Program and plays a critical part in strengthening how the Bank uses data to detect, assess and manage financial crime risks. As a Data Engineer, you&apos;ll build and maintain the data products that underpin key financial crime capabilities. Your work will support customer risk assessment, transaction monitoring, sanctions screening, fraud detection, investigations, regulatory reporting and operational insights. This is a hands-on engineering role with strong exposure to modern data platforms, cloud technologies, data governance, and financial crime transformation initiatives. Working as part of an inclusive and collaborative team your key responsibilities will include:<ul><li>Design and build scalable data pipelines that support financial crime and fraud use cases.</li><li>Develop curated datasets that provide trusted information for risk management, investigations, reporting and analytics.</li><li>Integrate data from banking systems, payment platforms, customer applications, transaction monitoring tools, screening systems, APIs, SaaS solutions, and third-party providers.</li><li>Implement data quality controls to ensure accuracy, completeness and traceability.</li><li>Create and maintain data lineage across source systems, transformations, reports and regulatory outputs.</li><li>Support the development of customer risk models, detection rules, monitoring scenarios and analytical features.</li><li>Contribute to the governance of critical financial crime data assets and ensure compliance with privacy and security requirements.</li><li>Monitor and optimise pipeline performance, reliability and scalability.</li><li>Work closely with Financial Crime, Fraud, Technology, Data and Risk teams to deliver practical solutions that meet business and regulatory requirements.</li><li>Contribute to documentation, technical design artefacts, engineering standards and operational support activities.</li></ul> What sets you up for success<ul><li>At least four years&apos; experience in Data Engineering, Software Engineering, Platform Engineering, Site Reliability Engineering, or a similar technical discipline.</li><li>Experience designing and supporting production-grade data pipelines.</li><li>Strong SQL capability.</li><li>Proficiency in Python, Scala, Java, or Go.</li><li>Experience working with cloud-based data platforms such as Snowflake, Databricks, BigQuery, Redshift, or Synapse.</li><li>Experience with modern data engineering tools such as DBT, Airflow, Dagster, Fivetran, Airbyte, AWS DMS, or similar technologies.</li><li>A practical understanding of data governance concepts, including lineage, data quality, metadata management, and critical data elements.</li><li>Experience implementing data quality controls and resolving data issues in complex environments.</li><li>Familiarity with DevOps practices, automated testing, CI/CD pipelines, source control, and Infrastructure as Code.</li><li>Strong communication skills and an ability to work effectively with both technical and business stakeholders.</li><li>Exposure to AML/CTF, fraud prevention, customer risk assessment, transaction monitoring, regulatory reporting, or financial crime technology platforms will be particularly valuable.</li></ul> What we can offer youThere&#x2019;s life at work, and life outside of work &#x2013; and we understand that. That&#x2019;s why we offer an extensive range of employee benefits.<ul><li>Enjoy flexible work arrangements.</li><li>Be supported with leadership and professional development, such as education assistance, mentoring, and emerging leadership programs.</li><li>Generous discounts on home loans, personal loans, insurance and other banking products and services.</li><li>An incentive scheme for exceptional performance, up to two weeks&#x2019; additional purchased leave per year, and novated lease program.</li><li>12 weeks paid parental leave for the primary care giver, and three weeks for the non-primary care giver.</li><li>Two days&#x2019; paid volunteer leave each year to use with a community partner of your choice.</li><li>Employee social clubs in our Perth and Coffs Harbour corporate offices.</li></ul> About usAre you looking for a career with endless opportunities? There&#x2019;s more to us than banking. We are a competitive Australian retail bank with customer-centricity at the heart of everything we do. P&amp;N Group is amongst the largest customer-owned banking organisations in Australia, represented by P&amp;N Bank in Western Australia and BCU Bank in New South Wales and southeast Queensland. Our purpose is to enrich the lives of our customers and their communities. Our culture is the sum of how we do things &#x2013; and we believe it&#x2019;s a real point of difference. Our culture is shaped by each and every one of us and by joining us, you will shape it too. We empower our people, mistakes are seen as an opportunity to learn, and we encourage diverse thinking. We are driven by a shared purpose and come together to build a workplace of trust and belonging for all. We continue to transform, shape, and develop the products, services, digital tools, and experience we offer our customers of today and tomorrow. To help us achieve our ambitious plans, we&#x2019;re looking for talented individuals to join our teams across all three states and all areas of our organisation. What does our recruitment process look like?The process can include a phone screen, virtual and/or face-to-face interview, psychometric testing, reference checks, and all relevant background checks. At P&amp;N Group, we are committed to creating an inclusive employee experience and better understanding the needs of our customers. We support this through employee networks, flexible work options, mentoring and initiatives that strengthen inclusion and cultural understanding across the organisation. We welcome and encourage applications from people of all backgrounds, identities, and lived experiences. This includes people who identify as LGBTQIA+, people with disability and/or who are neurodivergent, Aboriginal and/or Torres Strait Islander peoples, and people of all genders, ages and cultural backgrounds. If you require adjustments or flexibility during the recruitment process, please contact our Talent Acquisition team at recruitment@pnbank.com.au. We&#x2019;ll work with you to support your participation. To find out more about what it&#x2019;s like to work with us, visit https://www.pnbank.com.au/about/careers/, or meet some of our people here https://www.youtube.com/watch?v=ae8tyBGYofI. The closing date for applications is 16th October 2026.(Please note that candidate screening and interviews may be completed prior to advertisement closure date.)

At Bending Spoons, we&#x2019;re striving to build one of the all-time great companies. A company that serves a huge number of customers. A company where team members grow to their full potential. A company that functions at unparalleled levels of effectiveness and efficiency. A company that creates value for shareowners at an extraordinary rate. And a company that does so while adhering to high ethical standards. In pursuit of this objective, we acquire and improve digital businesses, not to sell on, but to own and operate for the long term. The transformations we make are often deep&#x2014;designed to speed up innovation, benefit customers, and strengthen business performance. Here, hierarchy is minimal and teams are small and talent-dense. We operate established products with the ambition, agility, and urgency of a startup. Across the company, we integrate AI deeply into how we work so that human judgment and machine intelligence reinforce each other. For a talented, driven, and collaborative individual, working at Bending Spoons is an opportunity to learn, make an impact, and progress their career at an exceptionally high rate. That&#x2019;s our promise to such a candidate. A few examples of your responsibilities<ul><li>Design and improve data pipelines. Contribute to the design and evolution of data systems&#x2014;ensuring data is accurate, reliable, and efficiently processed across diverse tech stacks.</li><li>Ensure data correctness and scalability. Work closely with software engineers to validate data, define metrics, and improve the robustness of reporting and analytics systems.</li><li>Develop internal data products and tooling. Help build scalable solutions (e.g., reporting engines, forecasting tools) used by product teams across the company.</li><li>Support platform-wide decision-making. Partner with multiple teams to provide the analytical and modeling backbone for business planning and performance tracking.</li><li>Leverage AI to accelerate work and uncover insights. Use AI tools to move faster, surface ideas and opportunities, and study competing products and trends. </li></ul>What we look for<ul><li>Reasoning ability. Given the necessary knowledge, you can solve complex problems. You think from first principles, and structure your ideas sharply. You resist the influence of biases. You identify and take care of the details that matter.</li><li>Drive. You&#x2019;re extremely ambitious in everything you do&#x2014;and your initiative, effort, and tenacity match the intensity of your ambition. You feel deeply responsible for your work. You hold yourself to a high&#x2014;and rising&#x2014;bar.</li><li>Team spirit. You give generously and without the expectation of receiving in return. You support the best idea, not your idea. You&apos;re always happy to get your hands dirty to help your team. You&#x2019;re reliable, honest, and transparent.</li><li>Proficiency in English. You read, write, and speak proficiently in English. </li></ul>What we offer<ul><li>Incredibly talented, entrepreneurial teams. You&#x2019;ll work in small, result-oriented, autonomous teams alongside some of the brightest people in your field.</li><li>An exceptional opportunity for growth. We go to great lengths to hire individuals of outstanding potential&#x2014;then, our priority is to put them in the ideal position to thrive. Spooners in their 20s lead products worth hundreds of millions of dollars. And if you&#x2019;ve got what it takes, you&#x2019;ll soon be playing an essential role in major projects, too.</li><li>All. These. Benefits. Flexible hours, remote working, unlimited backing for learning and training, top-of-the-market health insurance, a rich relocation package, generous parental support, and a yearly retreat to a stunning location. We help each Spooner set up the conditions to do their best work.</li><li>Competitive pay and access to company equity at a discount. Typical annual salary offers range from &#xA3;85,797 to &#xA3;151,436 in London and from &#x20AC;66,065 to &#x20AC;107,837 elsewhere in Europe. The lower end of these ranges applies to candidates with little or no relevant experience, while exceptionally experienced candidates may receive offers of up to &#xA3;316,052 in London or &#x20AC;240,330 elsewhere in Europe. Candidates offered a permanent contract may choose to receive part of their compensation in discounted company equity. </li></ul>Commitment &amp; contract Permanent or fixed-term. Full-time or part-time. Location Milan (Italy), London (UK), Madrid (Spain), Warsaw (Poland), or fully remote from eligible countries. The selection process In our screening process, we prioritize verifiable signals of excellence, regardless of seniority. There are no preferential paths beyond what your application demonstrates, and we evaluate every candidate through the same process. Some people hold back because they feel they lack experience or have an &#x201C;imperfect&#x201D; CV. If you like the role and believe you could excel over time, don&#x2019;t self-reject. All applications go through our careers page, which is the only way to be considered. If you pass our screening, you&#x2019;ll be asked to complete one or more tests. They are challenging, may involve unfamiliar problems, and can take several hours. To learn more about what to expect throughout the selection process, you can find additional information here. We set the bar high and won&#x2019;t extend an offer until we&#x2019;re confident we&#x2019;ve found the right candidate. This is why a job may remain open for months or be reposted several times. We consider all applicants for employment and provide reasonable accommodations for individuals with disabilities&#x2014;please let us know through this form. Before you apply If you&#x2019;ve applied before but didn&apos;t receive an offer, we recommend waiting at least one year before applying again. Bending Spoons is a demanding environment. We&#x2019;re extremely ambitious and we hold ourselves&#x2014;and one another&#x2014;to a high standard. While this tends to lead to extraordinary learning, achievement, and career growth, it also requires significant commitment. To help you ramp up quickly and set yourself up for success, we expect you to spend most days in our Milan office during your first few months with us, regardless of your long-term work location. It&#x2019;s the best way to rapidly absorb our company culture and build trust with your new teammates. We&#x2019;ll support you with generous travel and accommodation assistance. After that, you&#x2019;re welcome to work from one of our offices, or remotely from approved countries&#x2014;depending on what we agree at the offer stage. If the role speaks to you and you&#x2019;re excited to give your best, we&#x2019;d love to hear from you. Apply now&#x2014;we can&#x2019;t wait to meet you.

Data scientist

Job Description adesso Belgium is looking for a data scientist (2) to support our customer in building an AI Agent Platform Data Foundations. Customer Info Our customer is an international, independent provider of indirect procurement services. Job Requirements Preferred start date: 1xASAP and 1x January 2027 Duration: 12 months Rate: depending on your location Time Zone: CET Your role Build the data and context layer that powers the customer&apos;s procurement AI agent platform &#x2014; canonical models, knowledge graph, semantic/taxonomy layer, and the retrieval and evaluation pipelines agents depend on. This is production infrastructure from day one, not a proof of concept: versioned, tested, and built for multiple tenants. You Will Work On <ul><li>Data products &amp; canonical modeling &#x2014; Design and deliver the first reference data products (Supplier Master, Spend Cube, Contract Register) end to end, from source ingestion through the canonical model.</li><li>Knowledge graph &amp; ontology &#x2014; Stand up and operate the platform and working graphs (ontology, reference data, tenant separation); own the graph-plus-vector retrieval design, deciding per source whether data is represented as entities/relationships, embeddings, or both.</li><li>Master data &amp; semantic layer &#x2014; Build matching rules, golden records, and stewardship processes for Suppliers, Contracts, and Categories; contribute to the business glossary and taxonomy-to-ontology mapping.</li><li>Extraction &amp; evaluation &#x2014; Build document-extraction pipelines (e.g., from SharePoint sources) with confidence scoring and human review for uncertain cases; build and maintain labelled evaluation datasets and accuracy benchmarks against agreed thresholds.</li><li>Connector framework &#x2014; Build source connectors (starting with Fabric data products and master data golden records) so new sources can be onboarded without modifying the graph core or query service.</li><li>Quality feedback loop &#x2014; Implement the mechanism routing agent overrides, failures, or low-confidence retrievals back to data owners so data products improve over time rather than decay.</li><li>Engineering practice &#x2014; Work exclusively in the GitHub/Azure environment; ship via pull request with CI (build, tests, security scan, evaluation fixtures); version all schemas, connector contracts, and extraction configs. </li></ul>Hard Skills Required Experience <ul><li>Demonstrated experience taking a knowledge graph system to production (not just prototyping) &#x2014; schema design, query performance, tenant/data isolation - Using Neo4J and Python</li><li>Strong background in semantic modeling: ontologies, taxonomies, business glossaries, and their relationship to graph and canonical data models.</li><li>Hands-on experience with semantic web standards and technologies including OWL/OWL2, RDF, RDFS, SPARQL, ontology lifecycle management, taxonomy alignment, and semantic reasoning.</li><li>Experience building data products and master-data pipelines (entity matching, golden-record consolidation, stewardship workflows).</li><li>Experience designing and implementing hybrid retrieval architectures combining graph databases (e.g., Neo4j) and vector databases to support semantic search, RAG, and AI agent workloads.</li><li>Experience with retrieval architectures combining graph and vector/embedding approaches.</li><li>Experience building and maintaining labelled evaluation datasets and measuring extraction/model accuracy against a threshold.</li><li>Proficiency with modern data/ML engineering practices: version control, CI/CD, automated testing, containerized deployment</li><li>Experience with Microsoft Fabric and SharePoint-based document extraction pipelines. </li></ul>Soft Skills <ul><li>Fluent in ENG</li><li>Open to travelling if needed (EU), this position is fully remote</li><li>Collaborative mindset, ideally with a proven similar work experience </li></ul> Why join adesso Belgium? <ul><li>Work in an international group with strong local expertise in Belgium.</li><li>Collaborate with cross-functional teams to deliver trusted, compliant, reusable data products.</li><li>Flexible freelance setup with the support of a growing adesso Belgium community.</li></ul>

Freelance Data Scientist with Ontology and Graph expertise

<div class="content-intro"><div>
About <a href="https://himalayas.app/companies/eve">Eve</a> <a href="https://himalayas.app/companies/eve">Eve</a> is redefining legal technology for plaintiff law firms, and we're building the team that will take us there. We help firms handle more cases, recover more for clients, and grow with AI that works across every stage of a case, from intake through resolution. The next generation of great plaintiff firms will be AI-Native, and <a href="https://himalayas.app/companies/eve">Eve</a> is how they get there. But what makes <a href="https://himalayas.app/companies/eve">Eve</a> different isn't just the product. It's how we build it. If you're someone who takes ownership, stays curious, and wants to build AI that's already changing how law is practiced, this is where you belong.
Product-market fit: <a href="https://himalayas.app/companies/eve">Eve</a> is trusted by over 1000+ law firms, and we’re growing fast. Backed by top investors: We’ve raised over $160M from world-class partners including Spark Capital, Andreessen Horowitz(A16z), Menlo Ventures, and Lightspeed. Built by a world-class team: Engineers, designers, and operators from places like Scale, Meta, Airbnb, Cruise, Square, Rubrik, and Lyft are building <a href="https://himalayas.app/companies/eve">Eve</a> from the ground up. AI-Native from day one: We’re on the bleeding edge of AI, collaborating directly with teams at OpenAI and Anthropic to build best-in-class AI workflows tailored for legal work. Explosive growth: We are growing 2X revenue Quarter over Quarter.
</div></div><h3>The Role</h3><a href="https://himalayas.app/companies/eve">Eve</a> is doubling revenue quarter over quarter, and the platform is being built to keep pace. A medallion architecture is in place on a Terraform-managed Snowflake footprint. Most of what goes on top is still ahead: ingestion and orchestration built for the volume coming, reliability practice, the access and governance model, and the standards every contributor works inside.The data spans product usage, case and firm data, and every go-to-market system <a href="https://himalayas.app/companies/eve">Eve</a> runs on. Analytics engineers and business analysts build models and reporting on top of it, AI agents query it directly, and leadership makes calls on it weekly. When a pipeline fails quietly, all three inherit the mistake.You'll own the pipelines carrying all of that, end to end, from an ambiguous ask through to production. Moving nightly rebuilds onto incremental patterns. Deciding how a new source gets ingested and what happens when it changes shape. Building the alerting that catches a broken model before anyone downstream does, and being the one who picks it up when it breaks. You'll have real say in how the platform gets built. You'll work on our central team and report to the Head of Data Engineering, who reports directly to the CEO. Data is a first-class function at <a href="https://himalayas.app/companies/eve">Eve</a> and the fuel to drive our future growth.<h3>What You'll Do</h3><h3>Build and run the platform</h3><ul>
<li>Own ingestion through Fivetran, third-party connectors, and custom extraction where no connector exists</li>
<li>Own orchestration across dbt platform and GitHub Actions, own materialization strategy and model performance, move critical models off nightly full rebuilds onto incremental patterns, and cut latency where decisions are waiting on stale data</li>
<li>Build source-schema change detection, so an upstream field change surfaces as an alert before it reaches a report</li>
<li>Stand up observability: freshness SLAs on critical tables, alerting on failure and drift, and an incident path with clear ownership</li>
<li>Be a first responder when pipelines break, and drive the fix upstream so the same failure doesn't recur</li>
<li>Manage pipeline compute cost, and make the tradeoffs between freshness and spend explicit rather than accidental</li>
<li>Share Snowflake administration: implementing the role-based access model, security and network policies, data masking and PII controls, and storage organization</li>
<li>Extend the medallion architecture and the Terraform-managed footprint, including full separation of development and production</li>
<li>Contribute to the foundational modeling layer the Analytics Engineers build on: source-to-staging patterns, conformed dimensions, shared entities, and SCD patterns that make history reliable</li>
</ul><h3>Raise the bar</h3><ul>
<li>Build and maintain the development environments and CI that let analysts contribute models safely, and review their contributions so more of the company can build on the foundation</li>
<li>Build the tooling and setup that gets a new engineer or analyst productive in days, not weeks</li>
<li>Administer the data tooling stack: access, integrations, and the connective work between systems</li>
<li>Use AI-assisted development as part of how you work: Claude Code skills, agents, and evals, held to the same review bar as anything else</li>
<li>Document as you build. If it isn't written down, it isn't done</li>
</ul><h3>What We're Looking For</h3><ul>
<li>5+ years in data engineering, owning production systems other people depended on</li>
<li>Strong Python and SQL, with production experience across ingestion (Fivetran or similar), orchestration (dbt platform, GitHub Actions, or Airflow), and cloud infrastructure</li>
<li>Solid Snowflake: access control, warehouse sizing, query performance, and cost management</li>
<li>Practical dbt: incremental models, testing, macros, and a git-based workflow with CI. Experience building SCD tables from multiple sources</li>
<li>Comfort in a Terraform-managed environment. Infrastructure changes go through code review here, not the Snowflake console</li>
<li>You've built reliability practice where none existed: alerting, freshness SLAs, incident response, schema change detection</li>
<li>Proficiency with AI-assisted development such as Claude Code, including agentic pipeline design and skill-based workflows, and comfort integrating tools via MCP servers</li>
<li>Able to tell a stakeholder what broke, what it affected, and when it'll be fixed, without the jargon</li>
<li>Comfort building where the playbook doesn't exist yet</li>
</ul><h3>Nice to haves:</h3><ul>
<li>Experience in a regulated or high-sensitivity data environment (legal, healthcare, financial services)</li>
<li>Experience with streaming or near-real-time ingestion, and knowing when it isn't worth it</li>
<li>Exposure to Iceberg, Parquet, or unstructured data at scale</li>
<li>B2B SaaS, especially selling to small and mid-sized businesses or professional services firms</li>
</ul><div class="content-pay-transparency"><div class="pay-input">
<div class="description"><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div>For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. This salary range may be inclusive of several career levels at <a href="https://himalayas.app/companies/eve">Eve</a> and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and location.</div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>
<div class="title">US Salary Range</div>
<div class="pay-range">$185,000—$210,000 USD</div>
</div></div><div class="content-conclusion">
<div class="section page-centered">
<h3>Benefits</h3>
💰 Competitive Salary &amp; Equity
<h3>💹 401(k) Program with Employer Matching</h3>
⚕️ Health, Dental, Vision and Life Insurance 🩼 Short Term and Long Term Disability 🚗 Commuter Benefits* 🧑‍💻 Autonomous Work Environment 🖥️ Workplace Setup Reimbursement 🏠 Telecomm Stipend 🏝 Flexible Time Off (FTO) + Holidays 🚀 Quarterly Team Gatherings 🥪 In office Perks*
*In office employees only
</div>
<div class="section page-centered">
<a href="https://himalayas.app/companies/eve">Eve</a> Legal is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation during the application process, reach out to your recruiter.
We may use artificial intelligence (AI) tools to support parts of the hiring process. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
</div>
</div>Originally posted on <a href="https://himalayas.app">Himalayas</a>

Job Title: Senior Data EngineerLocation: UK (Hybrid/Remote)Salary: &#xA3;60,000 - &#xA3;70,000 per annum + BenefitsOur professional services customer is embarking on an exciting digital transformation. Having recently designed and built a modern data platform with an external delivery partner, now ready to transition to full internal ownership. As such they seek a hands-on Senior Data Engineer to take technical ownership of this ecosystem, driving BAU, development, and future scaling. The RoleAs Senior Data Engineer, you will bridge the gap between external implementation consultancy and our internal business users. Initially, you will work closely with external partners to manage a seamless knowledge transfer. Post-transition, you will assume full responsibility for operating, supporting, and evolving the data platform.This is a highly collaborative, technical role where you will manage everything from data ingestion and pipeline orchestration to back-end database development and dimensional modelling. Key Responsibilities<ul><li>Technical Ownership: Take the reins of the newly implemented data platform, ensuring smooth production support, monitoring, security, and data reconciliation.</li><li>Data Pipeline Architecture Development: Operate and develop robust data ingestion pipelines, SQL-based transformations, and complex business logic.</li><li>Data Warehousing: Design, maintain, and optimise data warehouse structures, data cubes, and dimensional models to support business intelligence.</li><li>Collaboration &amp; Transition: Work pragmatically with our external data consultancy during the transition phase to ingest the existing solution and establish best practice internally.</li></ul> Skills &amp; Experience Required<ul><li>Core Data Engineering: Substantial hands-on experience designing, building, and operating production data warehouses or modern data platforms.</li><li>SQL and deep experience in back-end database development.</li><li>Data Architecture: A background in Data Warehousing, Data Cubes, and dimensional modelling.</li><li>Pragmatic Mindset: A proven ability to understand, take over, and support existing third-party solutions with a proactive, problem-solving attitude.</li></ul> Desirable Extras<ul><li>Familiarity with legal finance and practice-management platforms.</li><li>Experience with Microsoft Fabric development is highly desirable. Alternatively, you may have an Azure Data engineering background and can upskill/adapt to Fabric quickly.</li></ul> What We Offer<ul><li>The opportunity to shape and own a modern enterprise data estate from the ground up.</li><li>A supportive, forward-thinking environment with exposure to the latest Microsoft data technologies.</li><li>Competitive salary (&#xA3;60-70k) and benefits package to match your experience.</li><li>A remote first working environment with occasional travel to the West Midlands.</li></ul> For further information or a confidential discussion on the role contact Dave Flynn at Meraki Talent today: david.flynn@merakitalent.com / 01312972709

Role Profile Job title: Senior Data Engineer Reporting to: Head of Data and Analytics. Responsible for: Responsible for leading the design and delivery of scalable data integrations using Azure Logic Apps, and related Azure services. Ensures reliability, quality, and governance of integration workflows, and contributes to continuous improvement and DevOps deployment practices. Provides technical guidance and mentoring to junior team members to support their development and uphold best engineering standards. Based at: Remote with travel to Portsmouth and London as required (circa once per month). At least once a month in London for team face to face. Scope: This senior role covers all integration pipelines and automations that support data movement across Bell. You will design, implement, and optimise integration workflows using Azure services, Logic Apps And Microsoft Fabric. You will ensure governance, quality, and scalability in all integration processes. Purpose As a Senior Data Integration Engineer, you will work closely with the Data and Analytics Team, and other stakeholders across the business to ensure seamless data accessibility and usage across the organisation. Role <ul><li>Design, develop, and maintain scalable, robust data integrations using Azure Logic Apps, Azure Storage Accounts Azure API Management, Microsoft Fabric, and other Azure Services.</li><li>Implement integration patterns such as event-driven workflows, API-based integrations, and scheduled orchestrations.</li><li>Ensure high availability, scalability, and security of integration workflows.</li><li>Collaborate with IT, and system users to understand business requirements and ensure data accessibility and integrity.</li><li>Monitor integration solutions, troubleshoot failures, and proactively improve reliability.</li><li>Lead continuous improvement initiatives, driving adoption of best practices and emerging Azure integration technologies.</li><li>Support DevOps processes using Azure DevOps for CI/CD automation, version control, and deployment of Azure resources.</li><li>Provides technical guidance and mentoring to junior team members to support their development and uphold best engineering standards.</li><li>Ensure data security and compliance with industry standards and regulations, such as GDPR.</li><li>Document data processes and workflows for both technical and non-technical audiences. </li></ul>Person <ul><li>Bachelor&#x2019;s or Master&#x2019;s degree in Computer Science, Information Technology, Data Science, Engineering, or a related field.</li><li>5+ years of experience in data integration, automation, or data engineering roles.</li><li>3+ years hands-on experience using Azure Logic Apps (essential), but Power Automate experience will be considered.</li><li>Strong experience working with Azure Services such as Storage Accounts, Key Vault, Azure Functions, API Management.</li><li>Experience of developing Analytics solutions using Microsoft Fabric or comparable Azure PaaS services, Azure Data Factory, Synapse etc.</li><li>Experience building and deploying Azure solutions using Azure DevOps pipelines and ARM/Bicep/Terraform templates.</li><li>Proficiency with REST APIs, authentication methods (OAuth, Managed Identities), and system-to-system integration patterns.</li><li>Knowledge of data modelling techniques and best practices.</li><li>Proven record of mentoring and working closely with junior members of a team, with desire to take on future line management responsibilities.</li><li>Experience of using Purview and Power BI is also Desirable, but not essential.</li><li>Desirable certifications, DP-203 Azure Data Engineer, DP-203 Azure Data Engineer, DP-600 Fabric Analytics Engineer Associate, AZ-900 Azure Fundamentals and DP-900 Azure Data Fundamentals.</li><li>Strong problem-solving skills with attention to detail and the ability to troubleshoot complex data issues.</li><li>Excellent communication and collaboration skills, able to work across teams to deliver solutions that meet business needs. </li></ul>Privacy Protecting your privacy and the security of your data is a longstanding top priority for Bell Integration. Please consult our Privacy Notice (click here) to know more about how we collect, use and transfer the personal data of our candidates.

Working model: fully remote from the UK. Employment: official full-time employment through a Luxoft Legal Entity. Why Luxoft?We offer a comprehensive benefits package to support your health, wellbeing, and financial security:<ul><li>Private medical &amp; dental insurance (BUPA)</li><li>Life insurance (3x salary) &amp; income protection</li><li>25 days annual leave + 8 public holidays + paid sick leave</li><li>Pension scheme (AEGON UK)</li><li>Interest-free company loan</li></ul> We are seeking a Senior Semantic Engineer to design and implement semantic data frameworks that provide a shared structure for enterprise data. In this role you will focus on building and maintaining ontologies and knowledge graphs, enforcing semantic validation rules for data quality, and collaborating with AI teams to integrate these semantic structures into intelligent applications. The position is industry-agnostic, emphasizing strong semantic web expertise and the ability to apply it in any enterprise context. Responsibilities:Design &amp; Maintain OntologiesDevelop and manage enterprise ontologies using technologies such as OWL and RDF. Work closely with business and domain experts to model real-world concepts, define relationships between data, and create a common language across the organization.Build Enterprise Knowledge GraphsCreate and maintain scalable knowledge graphs that connect data from multiple sources into a unified, searchable structure. Configure graph databases, load semantic data, and ensure high performance and reliability.Develop Semantic Queries (SPARQL)Write and optimize SPARQL queries to enable efficient data discovery, integration, and analytics. Support advanced search capabilities and help teams extract valuable insights from connected data.Ensure Data Quality &amp; GovernanceDefine and implement validation rules using standards such as SHACL and OWL. Ensure data consistency, integrity, and compliance with established modelling standards and business rules.Integrate Semantic Technologies with Enterprise SystemsPartner with software engineers, architects, and data teams to embed ontologies and knowledge graphs into data pipelines, APIs, applications, and enterprise platforms.Collaborate Across TeamsWork with business stakeholders, data stewards, AI/ML engineers, and technical teams to align semantic models with business needs. Promote adoption of semantic technologies through documentation, training, and knowledge sharing.Enable AI &amp; Intelligent ApplicationsSupport the integration of knowledge graphs and ontologies with AI solutions, including LLM-powered applications and AI agents. Help improve contextual understanding, knowledge retrieval, reasoning capabilities, and overall AI performance.Drive Best Practices &amp; InnovationStay up to date with emerging semantic web technologies, industry standards, and best practices. Contribute to the evolution of the organization&apos;s semantic architecture and establish guidelines for effective knowledge management. Skills:<ul><li>Ontology Design &amp; Maintenance: Design, develop, and maintain ontologies (using OWL/RDF or similar).</li></ul> <ul><li>Semantic Web Proficiency: Strong knowledge of semantic web technologies and standards - specifically, hands-on proficiency with OWL (Web Ontology Language) and RDF (Resource Description Framework) for ontology modelling, as well as SPARQL for querying graph data.</li></ul> <ul><li>Knowledge Graph Experience: Practical experience building or maintaining knowledge graphs or linked data systems in an enterprise setting.</li></ul> <ul><li>Data Modelling &amp; Integration Skills: A solid understanding of data modelling principles, data architecture, and integrating heterogeneous data sources. You should be capable of abstracting real-world entities into a semantic schema and mapping relational or NoSQL data to an ontology.</li></ul> <ul><li>Programming Skills: Proficiency in at least one programming or scripting language (such as Python, Java, or similar)</li></ul> Nice-to-Have Skills:&#x2022; Metadata Standards: Familiarity with metadata standards and vocabularies such as Dublin Core, schema.org, or other industry-specific ontologies/taxonomies. Experience applying these standards to annotate or integrate data&#x2022; AI and LLM Integration: Experience working on projects that involve AI agents or large language models, where ontologies or knowledge graphs were used to improve AI performance.&#x2022; Enterprise System Integration: Proven experience integrating semantic technologies into existing enterprise systems or data platforms.&#x2022; Tools &amp; Platforms: Hands-on experience with ontology and knowledge graph tools is beneficial. Languages:<ul><li>English: C1 Advanced</li></ul> Luxoft is committed to fostering a diverse and inclusive workplace.We show fairness to all throughout our talent acquisition and management process.

Semantic AI/ML Architect

We&#x2019;re On the Beach! Since 2003, we&#x2019;ve been rewriting the rules of how people discover, book and experience their perfect getaway. What started as connecting people to short-haul beach holidays has evolved into something much bigger: premium beach destinations, long-haul adventures and vibrant city breaks and that&#x2019;s just the beginning of our story. Powered by our deep-rooted entrepreneurial spirit, proprietary tech, curiosity and our incredible people, we&#x2019;re accelerating delivering best-in-class technology, the ultimate holiday app, and experiences that keep our customers coming back for more. Ready to build the future of travel with us? We operate a remote-first working model, with colleagues meeting in our Manchester office one day every two weeks. Please note that all applicants must be eligible to work full-time in the UK. About The Role We&#x2019;re looking for a Data Engineering Manager to help lead and grow our data engineering capability, shaping the platforms and practices that power analytics, insight and AI-driven innovation across the business. This is a great opportunity for someone who enjoys developing people as much as solving complex technical and platform challenges. You&#x2019;ll play a key role in helping us modernise how data moves through the business, from event-driven cloud data through to more traditional operational data sources, while supporting a talented team of engineers to do their best work. What You&#x2019;ll Be Doing Day To Day As Data Engineering Manager, you&#x2019;ll help lead a team responsible for building reliable, scalable and trusted data products across On the Beach. The role will be varied, with your time broadly split across three key areas: helping us consume and shape event-driven data, working with more traditional data sources and patterns, and supporting the growth and development of the team. You&#x2019;ll work closely with engineers, analysts, product teams, commercial teams and senior stakeholders to make sure our data platforms are robust, well understood and genuinely useful to the business. You&#x2019;ll Be Responsible For <ul><li>Leading, supporting and developing a team of data engineers, creating an environment where people can grow, share knowledge and deliver high-quality work</li><li>Shaping our approach to both modern event-driven data and more traditional data sources, helping improve how we ingest, process, model and make data available across the business</li><li>Supporting the design and evolution of our data platform, including pipelines, orchestration, observability, lineage, governance and data quality</li><li>Partnering with teams across Product, Engineering, Analytics and Data to understand business needs and translate them into scalable, maintainable data solutions</li><li>Helping define and improve data engineering standards around testing, monitoring, documentation, deployment and reliability</li><li>Making pragmatic technical decisions that balance delivery, platform quality, long-term maintainability and business value</li><li>Encouraging a culture of technical curiosity, continuous improvement and strong engineering practice across the team </li></ul>We&#x2019;re looking for someone who enjoys both technical leadership and people development. You&#x2019;ll be comfortable working across engineering detail, platform direction and stakeholder conversations. You&#x2019;ll Likely Bring Experience In <ul><li>Building, operating or leading cloud-based data platforms and production-grade data workflows</li><li>Working with data pipelines, data modelling, orchestration and modern cloud data tools such as Databricks, BigQuery, Spark or similar</li><li>Event-driven or streaming data patterns, as well as more traditional operational, legacy or non-event-driven data environments</li><li>Designing reliable, observable and well-tested data products that can be trusted by both technical and non-technical users</li><li>Coaching, mentoring or supporting engineers, with an interest in helping people develop and progress</li><li>Communicating technical ideas clearly and making pragmatic decisions in fast-moving environments </li></ul>Nice to have <ul><li>Experience with lakehouse architecture, medallion-style workflows or enterprise data modelling</li><li>Exposure to data governance, catalogue tooling, lineage, data quality frameworks or access management</li><li>Experience using AI tools to support engineering productivity, automation or data quality</li><li>Experience helping teams move from batch-heavy or legacy patterns towards more real-time, event-driven or cloud-native approaches </li></ul>Our Benefits We might be biased but we think our colleagues are pretty great. They&apos;re the people that have made On the Beach what it is today and continue to make it vibrant and successful tomorrow. That&apos;s why we offer a competitive benefits package, known as our Beach Perks, to all On the Beach colleagues. These Include <ul><li>25 days holiday plus your birthday off</li><li>Generous discount on holidays, plus you will receive 2 extra days annual leave on top of your holiday allowance to use whilst you&apos;re away on your On the Beach package holiday</li><li>Access to Learnerbly learning platform, plus workshops, courses and professional qualifications</li><li>Enhanced maternity, paternity, shared parental leave and adoption pay, plus other family friendly support</li><li>Employee Assistance Programme and free access to counselling</li><li>Simplyhealth Optimise Health Plan</li><li>Company Sick Pay scheme</li><li>Regular wellbeing events</li><li>Gym discount</li><li>Share Incentive Plan (SIP)</li><li>Death in Service cover</li><li>Onsite subsidised coffee shop</li><li>The Sandbox (our very own bar)</li><li>Food and drink discounts across a number of venues in Manchester City Centre</li><li>Regular social events</li><li>Cycle to Work scheme </li></ul>What Success Looks Like Success in this role is about building data pipelines and products that teams can trust. You&#x2019;ll help improve the reliability, quality and performance of our data platform, making it easier for teams across On the Beach to access and use the data they need. You&#x2019;ll reduce friction for downstream analytics and AI use cases by creating well-structured, well-tested and well-documented data products. You&#x2019;ll also contribute to a strong engineering culture within the data team, where standards are clear, pipelines are observable, and continuous improvement is part of how we work. What To Expect From Our Interview Process We&#x2019;ll run a multiple stage interview process, one stage of which will be an in-person interview at our fabulous Aeroworks office in Manchester city centre. We want to make sure everybody has the opportunity to perform at their best. If you require any reasonable adjustments during the interview process please let the Talent Acquisition team know and they will be happy to assist. Ways of working Our full time hours are 37.5 per week, but we don&apos;t have rigid working hours so you can find the working pattern that&apos;s right for you. We have core working hours between 10am - 4pm, so we can collaborate and enjoy the social side of work. We also have hybrid working so we all work from home and from our Aeroworks office in Manchester City Centre. We operate a remote-first working model, with colleagues meeting in our Manchester office one day every two weeks. Please note that all applicants must be eligible to work full-time in the UK We&apos;re On the Beach! One of the UK&apos;s largest online package holiday specialists, with significant opportunities for growth.

Data Engineering Manager

Job Title: Senior Data EngineerJob Location :London, UK ( 2 days a week in client office, 3 days remote)Job Type :Permanent, Contract, FTC Job Description: Mandatory Skillsets: Python, Snowflake, dBT, dremio, glue jobs, Apache iceberg, AWS ,SQL Key Responsibilities:&#x2022; Architect and Develop: Contribute to the platform&#x2019;s architectural design and build integration, modelling, data persistence, and analytical systems.&#x2022; Data Pipelines: Implement, maintain, and test robust data pipelines.&#x2022; Metadata Management: Develop and manage metadata processes and tools.&#x2022; Performance Monitoring: Ensure the stability and performance of data pipelines.&#x2022; Data Quality: Implement tools for data curation, metadata management, and quality assurance.&#x2022; Collaboration: Engage with business and technology teams to align the platform with organizational goals. Preferred Technical Skills:&#x2022; Programming: 5+ years of experience in Python/Java.&#x2022; Cloud Expertise: Strong understanding of AWS services (e.g., Lambda, Step Functions, ECS).&#x2022; Data Platforms: Hands-on experience with Snowflake and data stack technologies like Apache Iceberg and Spark.&#x2022; Workflow Orchestration: Exposure to tools like Apache Airflow, Prefect, Dagster, or DBT.&#x2022; Data Services: Familiarity with AWS Glue, Lake Formation, EMR, EventBridge, Athena, and similar services.&#x2022; Metadata Tools: Experience with tools like Amundsen, Atlas, DataHub, OpenDataDiscovery, or Marquez.&#x2022; RDBMS: Knowledge of PostgreSQL is a plus.&#x2022; Industry Experience: Proven experience building enterprise-wide data and analytics systems, preferably in financial services or asset management.

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