The application window is expected to close on: 10/30/2026 This is a US remote role Meet the Team The Attack Surface Management team is mission-critical to our security infrastructure. We aggregate, normalize, and correlate security data from over 120 sources to provide a unified view of our environment. Our team focuses on data ingestion, service uptime, and providing the actionable intelligence required to maintain our security posture. We are currently evolving our capabilities to incorporate AI-driven analysis to solve complex attribution challenges at scale. Your Impact In this role, you will become the Domain Expert for our data pipelines, moving us from reactive monitoring to proactive, data-driven security. You will own the data ingestion and attribution layer, ensuring that every asset and vulnerability is accurately traced to its owner, business unit, and criticality tier. This role is highly impactful, as it directly bridges the gap between raw, noisy security data and actionable findings, ultimately reducing our Mean Time to Remediation (MTTR). You will also have the opportunity to influence our transition toward AI-augmented data analysis and automated correlation. Responsibilities <ul><li>Design, build, and maintain robust data pipelines that ingest and normalize security data from a diverse array of sources (e.g., asset inventory, vulnerability scanners, cloud providers, and identity systems).</li><li>Operate and improve the attribution layer by implementing entity resolution and ownership assignment rules as version-controlled code.</li><li>Establish data quality monitoring to detect anomalies, missing data, or correlation failures, ensuring high visibility before issues impact end-users.</li><li>Develop automated correlation logic for complex infrastructure scenarios where conventional identification keys fail.</li><li>Collaborate with analysts and leadership to provide query support, reporting, and executive metrics that drive security program decisions. </li></ul>Minimum Qualifications <ul><li>Bachelor&#x2019;s degree in Computer Science, Data Engineering, Information Systems, or a related field plus 3+ years of relevant experience, or a Master&#x2019;s degree in a related field.</li><li>Proficiency in Python and SQL with a proven ability to write clean, maintainable code.</li><li>Demonstrated experience building and operating ETL/ELT pipelines using REST APIs and semi-structured data (JSON, YAML).</li><li>Experience with Git-based workflows, CI/CD, and data modeling standard processes.</li><li>Proficiency in AI/ML usage, including the ability to apply AI to data analysis and correlation tasks. </li></ul>Preferred Qualifications <ul><li>Exposure to security data domains such as vulnerability management, asset inventory, CMDB, or SIEM.</li><li>Experience with pipeline orchestration tools (e.g., Airflow, Dagster) and transformation frameworks (e.g., dbt).</li><li>Familiarity with graph data models, relationship-based asset modeling, or AI/ML-driven data analysis.</li><li>Cloud platform experience (AWS, Azure, GCP) and Infrastructure-as-Code (IaC) principles.</li><li>Experience operating within large-scale, federated, or decentralized enterprise environments. </li></ul>S&amp;TO Why Cisco? At Cisco, we&#x2019;re revolutionizing how data and infrastructure connect and protect organizations in the AI era &#x2013; and beyond. We&#x2019;ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint. Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you&#x2019;ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere. We are Cisco, and our power starts with you. Message to applicants applying to work in the U.S. and/or Canada: The starting salary range posted for this position is $103,200.00 to $146,800.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations, not including incentive compensation*, equity, or benefits. Individual pay is determined by the candidate&apos;s hiring location, market conditions, job-related skillset, experience, qualifications, education, certifications, and/or training. The full salary range for certain locations is listed below. For locations not listed below, the recruiter can share more details about compensation for the role in your location during the hiring process. U.S. employees are offered benefits, subject to Cisco&#x2019;s plan eligibility rules, which include medical, dental and vision insurance, a 401(k) plan with a Cisco matching contribution, paid parental leave, short and long-term disability coverage, and basic life insurance. Please see the Cisco careers site to discover more benefits and perks. Employees may be eligible to receive grants of Cisco restricted stock units, which vest following continued employment with Cisco for defined periods of time. U.S. employees are eligible for paid time away as described below, subject to Cisco&#x2019;s policies: <ul><li>10 paid holidays per full calendar year, plus 1 floating holiday for non-exempt employees</li><li>1 paid day off for employee&#x2019;s birthday, paid year-end holiday shutdown, and 4 paid days off for personal wellness determined by Cisco</li><li>Non-exempt employees** receive 16 days of paid vacation time per full calendar year, accrued at rate of 4.92 hours per pay period for full-time employees</li><li>Exempt employees participate in Cisco&#x2019;s flexible vacation time off program, which has no defined limit on how much vacation time eligible employees may use (subject to availability and some business limitations)</li><li>80 hours of sick time off provided on hire date and each January 1st thereafter, and up to 80 hours of unused sick time carried forward from one calendar year to the next</li><li>Additional paid time away may be requested to deal with critical or emergency issues for family members</li><li>Optional 10 paid days per full calendar year to volunteer </li></ul>For non-sales roles, employees are also eligible to earn annual bonuses subject to Cisco&#x2019;s policies. Employees On Sales Plans Earn Performance-based Incentive Pay On Top Of Their Base Salary, Which Is Split Between Quota And Non-quota Components, Subject To The Applicable Cisco Plan. For Quota-based Incentive Pay, Cisco Typically Pays As Follows <ul><li>.75% of incentive target for each 1% of revenue attainment up to 50% of quota;</li><li>1.5% of incentive target for each 1% of attainment between 50% and 75%;</li><li>1% of incentive target for each 1% of attainment between 75% and 100%; and</li><li>Once performance exceeds 100% attainment, incentive rates are at or above 1% for each 1% of attainment with no cap on incentive compensation. </li></ul>For non-quota-based sales performance elements such as strategic sales objectives, Cisco may pay 0% up to 125% of target. Cisco sales plans do not have a minimum threshold of performance for sales incentive compensation to be paid. The applicable full salary ranges for this position, by specific state, are listed below: New York City Metro Area $125,700.00 - $203,100.00 Non-Metro New York State &amp; Washington State $111,700.00 - $180,800.00 <ul><li> For quota-based sales roles on Cisco&#x2019;s sales plan, the ranges provided in this posting include base pay and sales target incentive compensation combined.</li><li> Employees in Illinois, whether exempt or non-exempt, will participate in a unique time off program to meet local requirements.</li></ul>

Data Engineer Remote

Amentum is a global leader in advanced engineering and innovative technology solutions, trusted by the United States and its allies to address their most significant and complex challenges in science, security and sustainability. Our people apply undaunted curiosity, relentless ambition and boundless imagination to challenge convention and drive progress. Our commitments are underpinned by the belief that safety, collaboration and well-being are integral to success. Headquartered in Chantilly, Virginia, we have approximately 50,000 employees in more than 70 countries across all 7 continents. We are seeking a skilled Fabric Data Engineer - Data Security &amp; Dev Ops Focus candidate with strong expertise in data security, DevOps practices, and Microsoft Fabric to design, build, and maintain secure, scalable, and highly automated data pipelines and infrastructure. In this role, you will leverage Microsoft Fabric&#x2019;s unified analytics platform (including Lakehouse, Data Factory, Spark, Real-Time Analytics, and OneLake) to ensure that data is collected, processed, stored, and accessed securely while applying modern DevOps principles for reliability, observability, and continuous delivery. You will partner closely with security, compliance, platform, data science, and engineering teams to embed security and operational excellence throughout the data lifecycle. This position is US remote telework and US Citizenship is required. Key Responsibilities <ul><li>Design, develop, and optimize secure ETL/ELT pipelines and data workflows using Microsoft Fabric (Data Factory, Spark notebooks, pipelines) as well as complementary modern tools (e.g., Airflow, dbt, Kafka). </li><li>Build and maintain Lakehouses, warehouses, and data platforms in Microsoft Fabric (OneLake) and related cloud services, with strong emphasis on encryption, access controls, sensitivity labels, and data isolation. </li><li>Implement and enforce data security controls including encryption at rest and in transit, tokenization, masking, row-level and column-level security, workspace and item-level permissions, and fine-grained access management within Fabric and connected Microsoft services. </li><li>Integrate security and compliance requirements (GDPR, CCPA/CPRA, HIPAA, SOC 2, ISO 27001, or industry-specific regulations) into Microsoft Fabric architectures and pipelines, leveraging Microsoft Purview and Fabric governance capabilities where applicable. </li><li>Apply DevOps practices to data infrastructure: design and maintain CI/CD pipelines for Fabric workspaces, notebooks, pipelines, and infrastructure-as-code (IaC); automate testing and deployment of data services. </li><li>Containerize supporting data applications and services (Docker) and orchestrate them where appropriate (Kubernetes or managed equivalents); manage infrastructure using tools such as Terraform, Azure Resource Manager, Bicep, or Pulumi. </li><li>Implement monitoring, logging, alerting, and observability for Fabric pipelines, Lakehouses, and related platforms (e.g., Azure Monitor, Fabric monitoring, Prometheus, Grafana, Datadog, or ELK stack) with a focus on security events and performance. </li><li>Automate security testing, vulnerability scanning, compliance checks, and policy-as-code within CI/CD pipelines for Fabric and supporting data infrastructure. </li><li>Monitor data pipelines for anomalies, unauthorized access attempts, and potential breaches; collaborate with security and platform teams on incident response and reliability improvements. </li><li>Develop and maintain data governance frameworks, including data cataloging, lineage tracking, classification, and retention policies with security and operational controls in mind (including Fabric and Purview integration). </li><li>Collaborate with stakeholders to translate security, reliability, and business requirements into technical solutions that balance usability, performance, protection, and maintainability on the Microsoft Fabric platform. </li><li>Document architectures, security controls, runbooks, and operational processes; contribute to security awareness and DevOps best practices across the data and platform teams. </li></ul>Knowledge, Skills &amp; Abilities <ul><li>Strong proficiency in SQL and at least one programming language commonly used in data engineering (Python preferred; Scala or Java a plus);</li><li>Familiarity with data governance, privacy regulations, and compliance frameworks; exposure to Microsoft Purview is a plus. </li><li>Solid understanding of distributed systems, data modeling, and performance optimization in secure, automated environments. </li><li>Excellent problem-solving skills and the ability to communicate technical security and operational concepts to both technical and non-technical audiences. </li></ul>Required Qualifications <ul><li>Bachelor&#x2019;s degree in Computer Science, Information Security, Engineering, or equivalent practical experience. </li><li>5+ years of hands-on experience as a Data Engineer building production data pipelines and platforms. </li><li>Hands-on experience with Microsoft Fabric (Lakehouse, Data Factory pipelines, Spark, OneLake) or closely related Microsoft analytics services (Synapse Analytics, Azure Data Factory, Azure Databricks). </li><li>Experience with cloud data platforms (especially Azure) and their security services (e.g., Microsoft Entra ID / Azure AD, Key Vault, Private Endpoints, Defender for Cloud, or equivalents). </li><li>Demonstrated experience implementing data security measures: encryption, access control, data masking/anonymization, sensitivity labeling, and secure data sharing. </li><li>Solid DevOps experience, including CI/CD pipelines (GitHub Actions, Azure DevOps, Jenkins, GitLab CI, or similar), infrastructure-as-code, containerization (Docker), and basic orchestration concepts. </li><li>Experience with monitoring, logging, and alerting tools in production environments. </li><li>US Citizenship required. </li></ul>Preferred Qualifications <ul><li>Experience with Spark (PySpark) is highly desirable. </li><li>Direct production experience with Microsoft Fabric workspaces, shortcuts, mirroring, Real-Time Analytics, or Data Activator. </li><li>Certifications such as Microsoft Fabric Analytics Engineer Associate, Azure Data Engineer Associate, Azure Security Engineer, AWS Certified Security &#x2013; Specialty, Kubernetes (CKA/CKAD), CISSP, CISM, or equivalent. </li><li>Hands-on experience with Kubernetes, Helm, or managed container services in data workloads. </li><li>Experience with modern data stack tools that support security and automation features (dbt, Fivetran/Airbyte with secure connectors, Great Expectations or similar for data quality/security checks). </li><li>Knowledge of zero-trust architecture principles and GitOps practices applied to Microsoft Fabric and Azure data platforms. </li><li>Experience with real-time streaming security considerations, secure API/data product design, and policy-as-code tools. </li><li>Prior work in regulated industries (finance, healthcare, government, etc.). </li></ul>Compensation Details: S110k - $130k The compensation range or hourly rate listed for this position is provided as a good-faith estimate of what the company intends to offer for this role at the time this posting was issued. Actual compensation may vary based on factors such as job responsibilities, education, experience, skills, internal equity, market data, applicable collective bargaining agreements, and relevant laws. Benefits Overview: Our health and welfare benefits are designed to support you and your priorities. Offerings include: <ul><li>Health, dental, and vision insurance</li><li>Paid time off and holidays</li><li>Retirement benefits (including 401(k) matching)</li><li>Educational reimbursement</li><li>Parental leave</li><li>Employee stock purchase plan</li><li>Tax-saving options</li><li>Disability and life insurance</li><li>Pet insurance </li></ul>Note: Benefits may vary based on employment type, location, and applicable agreements. Positions governed by a Collective Bargaining Agreement (CBA), the McNamara-O&apos;Hara Service Contract Act (SCA), or other employment contracts may include different provisions/benefits. Original Posting: 10/22/2026 - Until Filled Amentum anticipates this job requisition will remain open for at least three days, with a closing date no earlier than three days after the original posting. This timeline may change based on business needs. Amentum is proud to be an Equal Opportunity Employer. Our hiring practices provide equal opportunity for employment without regard to race, sex, sexual orientation, pregnancy (including pregnancy, childbirth, breastfeeding, or medical conditions related to pregnancy, childbirth, or breastfeeding), age, ancestry, United States military or veteran status, color, religion, creed, marital or domestic partner status, medical condition, genetic information, national origin, citizenship status, low-income status, or mental or physical disability so long as the essential functions of the job can be performed with or without reasonable accommodation, or any other protected category under federal, state, or local law. Learn more about your rights under Federal laws and supplemental language at Labor Laws Posters.

Fabric Data Engineer – Data Security & DevOps Focus

About Our Client:This organization operates in the residential energy sector, focusing on improving energy management and savings for customers across North America. It addresses challenges in residential energy efficiency and cleaner energy adoption by managing a large-scale virtual power plant, integrating device telemetry from millions of connected homes to optimize energy use and support sustainability goals. About the Opportunity:The STAFF DATA ENGINEER role is pivotal in shaping the organization&apos;s data platform strategy and infrastructure. This position is responsible for designing and implementing scalable, fault-tolerant data pipelines and a data lakehouse ecosystem that support analytics, operational insights, and machine learning. The role contributes significant technical leadership by mentoring engineers and influencing engineering practices to enhance data architecture and system reliability. Responsibilities:<ul><li>Define and implement long-term data architecture vision and standards.</li><li>Lead design and deployment of fault-tolerant batch and real-time streaming data infrastructure.</li><li>Collaborate with application and analytics teams to align data architecture and delivery.</li><li>Architect and optimize database systems including PostgreSQL Aurora and AWS Redshift.</li><li>Establish technical standards for data pipelines, monitoring, and data quality.</li><li>Participate in infrastructure management and on-call support.</li><li>Mentor data engineers and promote best practices and architectural reviews.</li><li>Evaluate and integrate modern data technologies and frameworks.</li></ul> Requirements:<ul><li>10+ years of software and data engineering experience with architectural leadership.</li><li>Bachelor&#x2019;s or Master&#x2019;s degree in Computer Science, Software Engineering, or equivalent.</li><li>Experience building and operating high-volume batch and streaming data architectures.</li><li>Expertise in scalable data lake architectures and managing device telemetry data.</li><li>Proficiency in database design, performance tuning, and query optimization.</li><li>Strong skills in Python, SQL, CI/CD, and Infrastructure as Code tools like Terraform.</li><li>Analytical problem-solving skills and ability to mentor and align teams.</li></ul> Pay Range and Compensation Package:<ul><li>Base salary range $170,000 to $220,000.</li><li>Eligible for a target annual bonus of 15% of base salary.</li><li>Participation in long-term incentive programs based on company performance.</li></ul> Benefits &amp; Perks:<ul><li>401(k) plan with employer contributions.</li><li>Fully remote work environment with home office allowance.</li><li>Flexible vacation policy and parental leave benefits.</li><li>Competitive health and wellness benefits.</li></ul> 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 a recruitment partner of this role. Please note that all employment decisions, including candidate assessment, interviews, hiring, compensation, and employment terms, are made exclusively by the hiring employer.

Staff Engineer, Data (Remote, US)

<h3>Why <a href="https://jobicy.com/company/socure" target="_blank" rel="noopener">Socure</a>?</h3>
Socure is building the identity trust infrastructure for the digital economy — verifying 100% of good identities in real time and stopping fraud before it starts. The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day.
We hire people who want that level of responsibility. People who move fast, think critically, act like owners, and care deeply about solving customer problems with precision. If you want predictability or narrow scope, this won’t be your place. If you want to help build the future of identity with a team that holds a high bar for itself — keep reading.
<h3>About the Role</h3>
We are looking for a Senior Data Engineer to join our Data Automation team. You will play a critical role in designing and building scalable data platforms and pipelines that power Socure’s identity verification products and analytics. This role is ideal for someone who has a strong passion for solving real business problems with data, and combines deep hands-on data engineering expertise with strong ownership.
<h3>What You'll Do</h3>
• Design and build batch and streaming data pipelines to support automated data ingestion, ML feature engineering and analytics across multiple product domains.
• Own end-to-end delivery of complex, ambiguous data initiatives, including architecture, implementation, testing, deployment, monitoring, and documentation.
• Develop and evolve the data platform to support large-scale data processing using modern cloud-native technologies.
• Automate data operations (validation, quality checks, alerting, backfills, and recovery workflows) to reduce manual effort and improve consistency.
• Optimize cost, performance, and reliability of data workloads.
• Partner closely with cross-functional teams (Data Science, Product, Engineering) to understand requirements, translate them into technical solutions.
• Evaluate and adopt new technologies (new processing engines, storage formats, orchestration tools, GenAI-assisted ingestion) to keep the platform modern and efficient.
<h3>What You Bring</h3>
• 5+ years of hands-on data engineering experience, building and maintaining production-grade data platforms and pipelines.
• Strong programming skills in general-purpose language (such as Python or Scala) for data processing, and SQL for data analytics.
• Deep experience with distributed data processing frameworks, such as Apache Spark, including performance tuning and optimization.
• Proven experience building data solutions using services on AWS (EMR, Lambda, s3, etc).
• Strong understanding of data modeling and data warehousing concepts, including partitioning, schema design for large-scale datasets.
• Experience operating and supporting production pipelines, including monitoring, alerting, incident response, and improving reliability over time.
• Solid foundation in software engineering practices, including version control, CI/CD, testing strategies, and code review.
• Strong communication and collaboration skills, with the ability to work effectively with both technical and non-technical stakeholders.
Preferred Qualifications
• Experience with streaming or near-real-time data processing (Kafka, Kinesis, etc).
• Hands-on experience with data orchestration tools (Airflow, Step Functions, etc).
• Familiarity with modern data platform patterns such as Data Lakehouse, Data Mesh, and large-scale data sharing across teams.
• Experience with prompt engineering using modern GenAI, Large Language Models (LLM).
• Experience mentoring other engineers and contributing to engineering-wide standards, best practices.

As a note; Socure cannot provide sponsorship now or in the future for this role.
Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your Socure recruiting partner directly.

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Senior Data Engineer

Staff Engineer (Data) | Fully remote (UK) | Up to &#xA3;125k We&apos;re partnered with a product-led scale-up in EdTech, with software used by thousands of schools across the UK. Underneath the product suite sits a large data platform, and on top of it a fast-growing set of AI and agentic features. They need a Staff Engineer to set the technical direction across all three. The role<ul><li>Own architecture for the data domain, from transactional databases (OLTP) through to analytics and reporting (OLAP) and the foundations their AI products run on</li><li>Set direction across multiple teams you don&#x2019;t manage, working closely with Product Directors and Technical Leads</li><li>Architect the infrastructure behind LLM orchestration, retrieval-augmented generation (RAG) and real-time model inference</li><li>Mentor senior engineers and technical leads, and help lead a genuine shift to AI-first ways of working</li><li>Influence as much as you design: expect to spend as much time getting stakeholders bought in as you do on the architecture itself</li></ul> Why it&#x2019;s worth a look<ul><li>Real scope and real ownership. This is a data architect role in practice, with a Staff Engineer title and the influence to match</li><li>An AI-first culture where the team already uses AI tools daily, and you&#x2019;ll help embed that into how they build</li><li>Fully remote within the UK, with occasional in-person catch-ups</li><li>A company where your decisions are visible and your impact is felt throughout</li></ul> What they&#x2019;re looking for<ul><li>A current Staff, Principal or Architect title, with architectural direction set across three or more teams</li><li>Strong data architecture and modelling experience (Star, Medallion) in cloud-native environments such as Snowflake</li><li>Depth in more than one data discipline (platform, analytics, data science or AI), and honesty about where you&#x2019;re lighter</li><li>Comfortable being the person in the room with product and commercial leaders, translating business goals into technical strategy</li><li>A view on how AI-first engineering will change the data ecosystem, ideally backed by worked examples</li></ul> This probably isn&#x2019;t for you if you want to ship code day to day, have spent your career in one layer of the stack, or prefer the technical side to the stakeholder side. If this sounds like you, or someone you know, apply here or message me directly for a confidential conversation. Staff Engineer (Data) | Fully remote (UK) | Up to &#xA3;125k

Staff Engineer (Data) | Fully remote (UK) | Up to £125k

Microsoft Fabric Data EngineerLocation: Remote (UK)Salary: &#xA3;60,000 - &#xA3;65,000 + BenefitsType: Permanent About the RoleWe are seeking an experienced Microsoft Fabric Data Engineer to join a growing data and analytics team. This is an opportunity to play a key role in the development of a modern, cloud-based data platform, leveraging Microsoft Fabric to deliver scalable, reliable, and business-critical data solutions.You&apos;ll be responsible for designing and building end-to-end data pipelines, developing Lakehouse and Warehouse solutions, optimising data models for analytics, and enabling high-quality reporting through Power BI. Working closely with stakeholders across the business, you&apos;ll help transform raw data into trusted, accessible, and actionable insight.This role is ideal for someone who enjoys ownership, is passionate about modern data architecture, and wants to help shape the future of an organisation&apos;s data capability. Key Responsibilities<ul><li>Microsoft Fabric Platform DevelopmentDesign, develop, and maintain scalable solutions within Microsoft Fabric.</li><li>Build and optimise Fabric Pipelines, Dataflows, Notebooks, Lakehouses, and Warehouses.</li><li>Implement robust data engineering standards and best practices across the platform.</li><li>Data Engineering &amp; IntegrationDevelop and maintain data ingestion pipelines from APIs, databases, flat files, and third-party applications.</li><li>Automate data processing workflows to improve efficiency and reduce manual intervention.</li><li>Create reusable transformation frameworks using Python, SQL, and Fabric notebooks.</li><li>Data Modelling &amp; AnalyticsDesign and develop scalable data models to support reporting and analytics requirements.</li><li>Enable efficient Power BI reporting through well-structured semantic models and optimised datasets.</li><li>Support the delivery of enterprise-grade analytics solutions.</li><li>Governance &amp; Data QualityImplement data quality controls, monitoring, and validation processes.</li><li>Support data governance initiatives, ensuring consistency, security, and compliance.</li><li>Maintain documentation, metadata, and lineage across data assets.</li><li>Stakeholder CollaborationWork closely with analysts, BI developers, software engineers, and business stakeholders.</li><li>Translate business requirements into scalable technical solutions.</li><li>Provide recommendations on improving data processes and architecture.</li></ul> Required Skills &amp; Experience<ul><li>EssentialHands-on experience with Microsoft Fabric.</li><li>Strong experience building Fabric Pipelines, Lakehouses, Warehouses, and Notebooks.</li><li>Advanced SQL skills and data modelling expertise.</li><li>Python experience for automation and data transformation.</li><li>Experience integrating data from APIs, databases, and cloud applications.</li><li>Power BI experience including semantic modelling and performance optimisation.</li><li>Understanding of modern data architectures including Lakehouse and Warehouse methodologies.</li><li>Experience working with Azure-based data platforms.</li><li>Strong stakeholder engagement and requirements gathering skills.</li><li>DesirableExperience with Azure Data Factory, Synapse Analytics, Databricks, or Azure DevOps.</li><li>Knowledge of CI/CD processes and Git version control.</li><li>Exposure to Microsoft Purview or other governance tools.</li><li>Experience within Energy, Utilities, Sustainability, Retail, Financial Services, or other data-intensive industries.</li><li>Microsoft Certifications such as:</li><li>DP-700 Microsoft Fabric Data Engineer Associate</li><li>DP-600 Microsoft Fabric Analytics Engineer Associate</li><li>PL-300 Power BI Data Analyst</li></ul> <ul><li>What We&apos;re Looking ForOwnership mentality with a passion for building scalable solutions.</li><li>Strong problem-solving and analytical skills.</li><li>Excellent communication and stakeholder management abilities.</li><li>Ability to work independently in a remote environment.</li><li>Curious, proactive, and committed to continuous improvement.</li><li>Pragmatic approach to balancing technical excellence with business priorities.</li></ul> <ul><li>BenefitsSalary: &#xA3;60,000 - &#xA3;65,000</li><li>Fully Remote Working</li><li>Flexible Hours</li><li>Private Healthcare</li><li>Generous Pension Contribution</li><li>Learning &amp; Development Budget</li><li>Microsoft Certification Support</li><li>25 Days Holiday + Bank Holidays</li><li>Career Progression Opportunities</li></ul>

Fabric Data Engineer

<h2>Who are we?</h2>Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that.We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft.We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us!<h2>Why this role?</h2>We’re building the foundational infrastructure that will define how the world thinks about and deploys AI, and we want the sharpest, most driven, and most curious people to help us do it. As the head of the Data Foundation pillar of our Analytics and Data Insights team, you’ll lead the team that makes Cohere’s data trustworthy, governed, and available: the warehouse every analytics surface runs on, the pipelines that keep it fresh, the access model that keeps it secure, and the agentic analytics layer that lets anyone at Cohere (and their agents) ask questions of governed data directly.Your team owns the full data lifecycle. You’ll run ingestion into BigQuery from internal and external data sources, orchestrate it in Airflow and Cloud Run, model the data warehouse in dbt, and serve the results through Looker, export APIs, and customer-facing analytics surfaces. Everything is provisioned as code in Terraform, and governance is part of the design: VPC service controls, IAM patterns, and documented access paths that let people and agents move fast without putting data at risk.This role is both highly visible and highly impactful, and you’ll inherit a solid structure on which to build the rest of the stack: a Terraform-provisioned warehouse framework, dbt modeling conventions, an alerting and incident-response practice, and documentation patterns to keep everything discoverable. The roadmap is set with big bets in flight: scaling that framework across the company, standing up an internal analytics agent with a real eval harness, and consolidating institutional knowledge into a self-correcting and self-maintaining system that keeps context centralized, current, and documented, rather than dispersed and in people’s heads.ResponsibilitiesAs the head of the Data Foundation pillar, you will:<ul style="min-height:1.5em"><li>Build and lead the team. Hire and grow a team of data and infrastructure engineers; set the technical bar; develop strong talent and raise team performance, building leadership capability beneath you.</li><li>Set the roadmap from company strategy. Own and sequence the Data Foundation roadmap: the warehouse buildout, the agentic analytics program, data governance, and the platform work that unblocks our other pillars. You’ll make the trade-offs and carry the cross-functional impact that comes with them.</li><li>Own the data platform end to end. Ingestion (managed connectors and an open-source connector framework), orchestration on Airflow and Cloud Run, warehouse modeling in BigQuery with dbt (raw, core, mart layers), and serving through Looker, export APIs, and semantic layers. All of it provisioned as code in Terraform.</li><li>Own data governance. Define how humans, service accounts, and agents get access to governed data: VPC service controls, IAM patterns, documented onboarding paths, audit logs, and sensitive requests (including legal holds) handled to deadline.</li><li>Operate for reliability. Run the alerting and anomaly-detection framework, own data freshness SLAs, lead incident response and postmortems, and turn every incident into a durable standard so the same class of failure doesn’t recur.</li><li>Lead the agentic analytics program. Wire the semantic layer into an internal analytics agent, build the eval harness that measures its accuracy, and make the eval-driven call on where AI earns its way into production. Apply the same discipline to automating data engineering work itself.</li><li>Set the standard for analytics across the company. The medallion framework, naming conventions, and testing patterns your team maintains become the way other teams ship analytics data. You’ll onboard new domains onto it and keep the docs accurate to how the systems actually work.</li><li>Partner across the org. Work with the North product and engineering teams on the analytics surfaces that ship in the product (including a customer-facing analytics export), with Business Insights on marts for the business, with Security on data governance, and with Legal on compliance-critical data requests.</li></ul><h2>Qualifications</h2>You may be a good fit, if you have:<ul style="min-height:1.5em"><li>10+ years of experience across data engineering, data infrastructure, or analytics platform work, with a strong management track record leading data platform or infrastructure teams</li><li>Serious hands-on history in data engineering or infrastructure before management. You can still read a Terraform plan, a dbt DAG, or an Airflow scheduler log and ask the question that matters</li><li>Production experience with cloud data warehouses (BigQuery, Snowflake, or similar), workflow orchestration (Airflow or similar), and infrastructure as code (Terraform or similar)</li><li>Depth in data modeling: you think in fact and dimension tables, raw/core/mart separation, and semantic layers, and you have opinions on where tests and contracts belong</li><li>A record of setting a team’s roadmap from company or function strategy and delivering outcomes that span teams, with the cross-functional partnerships to match</li><li>Operational excellence you can point to: alerting you trust, SLAs you meet, incidents you run to ground and write up so they teach</li><li>Exposure to data security and governance: IAM, access management, VPC service controls or equivalent, audit and compliance workflows</li><li>Genuine excitement about AI: you follow the research, have opinions, and are energized by building the data foundation an AI company (and its AI agents) runs on</li><li>Comfort operating in ambiguity, leading a multi-workstream roadmap, and working directly with executives on priorities</li></ul>If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply!<h2>Full-Time Employees at Cohere enjoy these Perks:</h2><ul style="min-height:1.5em"><li>A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch.</li><li>Full health and dental benefits, including a separate budget for mental health.</li><li>RRSP matching, 401K, Pension Scheme.</li><li>100% Parental Leave top-up for up to 6 months, for either parent.</li><li>Annual enrichment benefits:Arts &amp; culture, fitness/wellness, quality time, and a workspace improvement credit.Education &amp; learning stipend for conferences, courses, and coaching.</li></ul><ul style="min-height:1.5em"><li>6 weeks of paid vacation (30 working days!)</li><li>Budget for traveling to other offices if you are remote, plus an annual company offsite.</li></ul><h2>How and Where We Work:</h2><ul style="min-height:1.5em"><li>Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon.</li><li>For those in the office: a daily lunch program, plenty of snacks, and regular community and social events.</li><li>For those not near an office: a co-working benefit so you can work alongside others in your city.</li><li>Everyone receives a $500 home office stipend to set up your workspace properly.</li></ul>If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an<a target="_blank" rel="noopener noreferrer nofollow" href="https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit"> Accommodations Request Form</a>, and we will work together to meet your needs.We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider.Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our <a target="_blank" rel="noopener noreferrer" href="https://cohere.com/careers">official careers</a> page.

Senior Staff Data Engineer

Hi, I&apos;m Nishya, Head of Data and AI at Intact &#x2013; the world&apos;s leading software provider for the Testing, Inspection and Certification (TIC) industry. We&apos;re looking for a Senior Data Engineer to build the data foundation for the next generation of our product. We have years of operational data on audits, certifications, standards, evidence, findings and organizations. Much of it is still locked in systems built to run workflows. We want to turn it into a trusted, scalable product asset. You&apos;ll design the pipelines, models, quality checks, and infrastructure that make this data ready for analytics, product features, and AI/ML. This is not a reporting role or a ticket queue. You&apos;ll help build a modern data platform that becomes part of the product itself. It will connect legacy and modern systems as Intact transforms domain by domain. You&apos;ll work closely with me and with our Product, Engineering, and Applied AI/ML teams. Sounds exciting? We&apos;d love to hear from you. ARE YOU READY?<ul><li>Build reliable, scalable, and cost-efficient batch and incremental data pipelines, with near-real-time processing where it&apos;s needed.</li><li>Own Change Data Capture (CDC), incremental processing, and schema evolution, and make sure the data&apos;s history stays correct.</li><li>Own data contracts with source teams so schema changes stay manageable.</li><li>Design canonical analytical models for key business entities, events, and relationships.</li><li>Build reusable transformations with clear layers between raw, transformed, and consumption-ready data.</li><li>Design the data platform around how consumers use it, balancing performance, scalability, and cost.</li><li>Build and evolve the data quality and governance framework, covering testing, monitoring, lineage, ownership, and failure recovery.</li><li>Build self-serve patterns and documentation so teams can publish and consume data independently.</li><li>Provide trusted data for analytics, product features, and AI/ML use cases.</li><li>Design mechanisms for access control, retention, deletion, anonymization, and pseudonymization.</li><li>Monitor data pipelines and keep them fast and cost-efficient.</li><li>Treat data engineering as software engineering, with version control, code review, automated testing, infrastructure as code, and CI/CD.</li></ul> ARE YOU THE ONE?We care more about how you approach problems than about which tools you&apos;ve used. Here&apos;s what we have in mind. Technical foundation<ul><li>7+ years of building and running production data systems, ideally owning them from source to consumer.</li><li>Advanced SQL and Python (or another data engineering language), with a solid understanding of how your queries perform.</li><li>Clean, well-tested code that your teammates can easily maintain.</li><li>Strong dimensional, relational, and analytical data modeling, including tracking how data changes over time.</li><li>A degree in computer science, data engineering, or a related field, or equivalent practical experience.</li></ul> Architecture and data platforms<ul><li>Hands-on CDC experience (e.g., Debezium, AWS DMS, Fivetran, or native log-based CDC), including handling deletes, backfills, and schema changes.</li><li>Experience designing a modern cloud warehouse or lakehouse (e.g., Snowflake, Databricks, BigQuery, or Microsoft Fabric) with a strong focus on performance, scalability, and cost.</li><li>Experience with reusable ELT transformations (e.g., dbt) and orchestration tools (e.g., Airflow or Dagster).</li><li>Pipelines that can be rerun safely and recover predictably from failures.</li><li>A strong batch background, and the judgment to know when near-real-time processing (e.g., Kafka or a managed equivalent) is worth the extra complexity.</li></ul> Running data in production<ul><li>Docker, Terraform (or similar), and CI/CD as part of your everyday toolkit.</li><li>Monitoring, logging, and alerting built into everything you ship.</li><li>Cost and performance considered in every design decision.</li><li>Data quality, security, and governance built in from the start, covering contracts, validation, lineage, access control, and ownership.</li><li>A good understanding of privacy requirements such as the GDPR, including retention, deletion, and pseudonymization.</li></ul> How you work<ul><li>You&apos;re a systems thinker with pragmatic judgment and a strong sense of ownership, from design through operation.</li><li>You prefer simple solutions that deliver value early over complex ones that take months to land.</li><li>You&apos;re curious about the business meaning behind the data.</li><li>You speak up when you see a better way and stay open to other people&apos;s ideas.</li><li>You&apos;re fluent in English. German is a plus.</li></ul> Nice to have<ul><li>Experience with open table formats such as Apache Iceberg or Delta Lake.</li><li>Experience with a data catalog or lineage tool such as DataHub or OpenMetadata.</li><li>Experience preparing data for AI/ML, such as evaluation datasets, features, or retrieval pipelines.</li><li>Experience moving data out of legacy, workflow-oriented systems while they&apos;re still in use.</li><li>Experience consolidating data from many similarly structured source databases into a single analytical model.</li></ul> WHY US?<ul><li>A platform to shape. As one of the first data engineers in the Data and AI team, you&apos;ll help shape the platform and its standards from the start.</li><li>Work with purpose. Your work helps safeguard quality, safety, and sustainability worldwide.</li><li>An international team. You&apos;ll work closely with colleagues across Product, Engineering, and operations around the world.</li><li>Flexible work. Flexible work models, with a 100% remote option.</li><li>Lebring office perks. Food vouchers, free parking, and easy access to public transport.</li><li>Room to grow. We don&apos;t just allow personal development, we encourage it. Your growth is our gain.</li><li>Fair compensation. From &#x20AC;64,554 gross per year (full-time), with overpayment up to &#x20AC;85,000 depending on seniority and experience.</li><li>Start: As soon as possible.</li></ul>

Help Us Build The Future of Travel At Airalo, we&apos;re making it easier for people to stay connected wherever they travel. As the world&apos;s first eSIM store, we help millions of travelers access affordable mobile data in 200+ countries and regions around the world. Today, we&apos;re a team of 400+ people across 60+ countries, building a product used by travelers every day. We&apos;ve grown quickly, but we&apos;ve worked hard to keep what matters: trust, ownership, and the freedom for people to do great work without unnecessary layers or bureaucracy. We&apos;re fully remote by design, genuinely global, and united by a shared mission to make travel simpler for everyone. Your Next Destination <ul><li>Location: Remote, anywhere in Spain or the UK.</li><li>Contract:</li><ul><li>Spain: Full-time, permanent contrato indefinido via Deel (our employer of record in Spain)</li><li>UK: Full-time, permanent</li></ul><li>Benefits: Learn more about our benefits here in this link - https://airalo-public.notion.site/Benefits-25396a97ffca81fb9bc1f0be479f1be3?pvs=74 </li><li>Languages: English is our main working language day to day, so you&apos;ll need to be comfortable communicating in it both in meetings and async. </li></ul>Benefits Curious what it&apos;s actually like to work at Airalo? We&apos;ve put together a guide for each of the hubs we hire from most, covering our benefits, remote culture, employment setup, and what our team values most: <ul><li> Life at Airalo</li><li> Espa&#xF1;a : https://airalo-public.notion.site/life-at-airalo-espana </li><li> Life at Airalo</li><li> United Kingdom : https://airalo-public.notion.site/life-at-airalo-united-kingdom </li></ul>We&#x2019;re looking for a Senior Analytics Engineer to help shape how data is modeled and governed at Airalo, transforming first- and third-party data into clean, trusted, well-documented datasets that power decisions across product, marketing, finance, and commercial teams, serving 30+ million users and growing. This role carries particular weight in our finance and revenue domain: you&#x2019;ll steward the models finance relies on directly, including order-to-revenue flows and reconciliation against third-party systems such as our ERP, where precision and auditability matter as much as scalability. Our analytics engineering function is still maturing, so you&#x2019;ll have real ownership in establishing standards, defining our semantic layer, and shaping how data is structured as we scale globally, working closely with the rest of the data team to build a production-grade analytics platform on LightDash and beyond. What You&apos;ll Do <ul><li>Design, implement, and maintain data models using dbt within our cloud data warehouse, ensuring performance, cost efficiency, and alignment with business logic </li><li>Build and maintain finance and revenue data models, including order-to-revenue flows, recognition logic, and reconciliation against source-of-truth financial systems, that finance and commercial teams can rely on for reporting and forecasting </li><li>Own the order-to-revenue pipeline: ensuring every order correctly and traceably resolves into recognized revenue, with clear handling of refunds, adjustments, currency conversion, and edge cases </li><li>Collaborate with other analytics engineers and data engineers to build and scale ELT workflows that ensure data freshness and reliability for mission-critical reporting </li><li>Partner with Finance and the ERP systems integrator to validate that data models and definitions carry over correctly from legacy systems into the new ERP/EPM platform </li><li>Implement robust testing, documentation, and monitoring practices, acting as a steward of data quality and governance across the platform, with particularly high attention to detail in domains where small errors compound (e.g., revenue, finance) </li><li>Collaborate cross-functionally to translate complex business questions into scalable, production-ready data artifacts </li><li>Partner with the data analysts and domain leadership to drive the rollout and adoption of self-service analytics, ensuring business users can trust and independently explore the data models you build </li><li>Contribute to the evolution of our modern data stack, bringing curiosity and pragmatic judgment to new tools and approaches </li></ul>Must Haves <ul><li>Bachelor&apos;s/Master&apos;s degree in a quantitative field (statistics, economics, mathematics, computer science, or equivalent work experience) </li><li>Hands-on experience building finance and/or revenue data models, ideally including order-to-revenue or billing-to-revenue pipelines, revenue recognition logic, or financial reconciliation (ERP, billing platforms or similar) </li><li>5+ years in analytics engineering, data engineering, or analytics roles with significant modeling responsibilities </li><li>Strong SQL and data modeling skills, with demonstrated experience designing robust, scalable dimensional models </li><li>Exceptional attention to detail, especially when working with numbers that feed financial reporting, reconciliation, or external disclosure </li><li>Significant hands-on experience with dbt (Core or Cloud) for managing transformation logic, testing, and documentation </li><li>Familiarity with cloud data platforms (BigQuery) and data orchestration tools (Airflow, Dagster, or similar) </li><li>Experience working with modern BI platforms and semantic layers-LightDash experience is a strong plus </li><li>Track record of partnering with analysts and business stakeholders to translate requirements into well-structured data products </li><li>Strong communication skills, with the ability to explain complex data concepts to diverse audiences </li><li>Proactive self-starter who thrives on solving ambiguous problems and takes ownership from concept to production </li></ul>Nice To Have <ul><li>Experience in marketplace, telecom, or travel/mobility businesses </li><li>Background in B2C product companies with high-volume event data </li><li>Experience building analytics engineering capabilities in low-maturity data environments </li><li>Previous experience at a scale-up that went through hypergrowth </li><li>Experience defining and governing company-wide KPIs and metric frameworks </li><li>Experience working alongside or within a finance function (e.g., supporting FP&amp;A, revenue accounting, or audit processes) on data accuracy and traceability </li></ul>&#xA3;74,800 - &#xA3;112,200 a year At Airalo, we believe in roaming-free recruitment. Just as we provide clear connectivity for travelers, we provide clear salary ranges for our candidates. &#x1F30D; This role is remote and open to candidates across our supported locations in Europe. The range below reflects the full salary range for this role across the countries where it&apos;s available: &#x1F4CD; UK: &#xA3;74,800 &#x2013; &#xA3;112,200 &#x1F4CD; Spain: &#x20AC;77,600 &#x2013; &#x20AC;116,400 &#x1F4CD; Germany: &#x20AC;76,000 - &#x20AC;114,000 Your Home Destination: &#x1F6EB; Local market rates and cost of living vary. Your specific range within this band depends on where you&apos;re based, and there&apos;s room to discuss what&apos;s right for the person and the role. We&apos;ll walk through your range together on your first call with our Talent team so we&apos;re aligned for takeoff! &#x1F392;&#x2728; Why People Join Us &#x1F1EA;&#x1F1F8; Why people join us in Spain We started Airalo to make staying connected effortless, wherever you are in the world. Today, millions of travelers rely on our eSIMs, and many of the people building the product were customers first. Our team is united by a shared belief that great work happens when people are trusted to own what they do. As Airalo continues to grow, so do the opportunities to learn, take on new challenges, and make a real impact. For many of our teammates in Spain, it&apos;s the combination of stability, flexibility, and genuine work-life balance that makes Airalo feel like home. &#x1F1EC;&#x1F1E7; Why people join us in the UK We started Airalo to make staying connected effortless, wherever you are in the world. Today, millions of travelers rely on our eSIMs, and many of the people building the product first discovered us as customers. Our team spans 60+ countries, but what people often notice quickly is how work actually feels here. There&apos;s trust to own what you do, space to focus without constant layers of process, and a clear sense of what you&apos;re responsible for from day one. As Airalo continues to grow, people tend to stay for a mix of things: the chance to work on a product used globally, the autonomy to shape how they work, and the opportunity to keep taking on new challenges without getting stuck in one lane. Before You Hit Apply By applying, you acknowledge and agree that, in case of successful application, Airalo may request to run background checks as a condition for entering into an agreement with you. Rest assured that these checks will only occur upon your prior consent and at the end of the selection process, and will be strictly limited to what is allowed under the laws that are applicable to you. All data that you share or that we collect in connection with such checks will be processed in accordance with our Privacy Policy, available here: www.airalo.com/more-info/privacy-policy?srsltid=AfmBOooBT0rXAj1FaNelZ3VfN0wvhwzvAoxdtHnOKSVETpiSjiXVuycy We sincerely thank all applicants in advance for submitting their interest in this opportunity. Airalo is an equal-opportunity employer and values diversity, equity &amp; inclusion. We do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We are committed to providing reasonable accommodations upon request for individuals with disabilities throughout our job interview process. At Airalo, we use AI-assisted tools as part of our recruitment process. Your application will be reviewed using tools that help our recruiters analyze and organize CV information. These tools support, but do not replace, human judgment; all hiring decisions are made by humans. If you progress to an interview, we may use tools to generate AI-assisted notes - you can opt out of these. For more information on how we handle your data, please see our Privacy Policy: https://www.airalo.com/more-info/privacy-policy.

Senior Analytics Engineer, Finance

Ein Freund von uns sucht einen Data Platform Engineer (m/w/d), f&#xFC;r alle, die Cloud Platform Engineering mit dem Data- &amp; AI &#xD6;kosystem verbinden m&#xF6;chten. &#x25AB;&#xFE0F; Das UnternehmenWachsendes IT Beratungsunternehmen mit Fokus auf Data Analytics, moderne Cloud-Technologien &amp; digitale Gesch&#xE4;ftsprozesse. Kurze Entscheidungswege, anspruchsvolle Kundenprojekte und viel Gestaltungsspielraum. &#x25AB;&#xFE0F; Deine Aufgaben (u. a.)<ul><li>Aufbau &amp; Weiterentwicklung moderner Data- &amp; AI Plattformen</li><li>Entwicklung skalierbarer Cloud- &amp; Plattformarchitekturen</li><li>Aufbau &amp; Weiterentwicklung von Databricks Umgebungen</li><li>Automatisierung von Cloud Infrastrukturen mit IaC</li></ul> &#x25AB;&#xFE0F; Technologien (u. a.)<ul><li>Databricks, Unity Catalog</li><li>Azure /AWS, Python, APIs</li><li>Terraform, Git, CI/CD</li><li>Cloud Networking, IAM &amp; Security</li></ul> &#x25AB;&#xFE0F; Der Job macht dir Spa&#xDF;, wenn &#x2026;<ul><li>Du Erfahrung mit Cloud Infrastrukturen &amp; Platform Engineering mitbringst</li><li>Du bereits mit Databricks und dem Data-/AI &#xD6;kosystem gearbeitet hast</li><li>Du Lust auf Plattformarchitektur &amp; technische Kundenberatung hast</li><li>Du Erfahrung mit IaC, CI/CD, Networking &amp; Security mitbringst</li></ul> &#x25AB;&#xFE0F; Benefits (u. a.)<ul><li>Full Remote m&#xF6;glich</li><li>Weiterbildungen &amp; Zertifizierungen</li><li>Flexible Arbeitsmodelle &amp; Gestaltungsspielraum</li></ul> &#x25AB;&#xFE0F; Was kann man so verdienen?Je nach Erfahrung und technischem Background sind ca. 50k - 70k &#x20AC; m&#xF6;glich. Interesse geweckt? Einfach bewerben &#x1F642; Ich freue mich auf den Austausch!

Dateningenieur:in

About Courtyard Courtyard.io is the fastest-growing collectibles startup, ever. We are revolutionizing the world of collectibles trading by enabling instant liquidity and delivering a high-velocity, immersive experience. From trading cards to comics, we&apos;re redefining how people discover, collect, and unlock value. Courtyard is not just another marketplace. All assets are securely vaulted and fully insured, giving collectors peace of mind alongside unmatched speed and simplicity. Whether you&apos;re investing, discovering, or curating your dream collection, we&apos;ve built a platform that&apos;s trusted, simple, and built for speed. And we&apos;re just getting started. We&apos;re a remote-first company hiring across all functions to push the boundaries of what&apos;s possible in collectibles and digital ownership. Job Summary Courtyard is hiring a Staff Data Engineer to own the data foundation our pricing and ML run on, from raw external market data all the way to models making decisions in production. We price and buy back assets in real time off a fragmented external market. Turning that into something a model can safely consume, and keeping the model healthy once it&apos;s live, is the hardest data problem here. You&apos;ll be the senior-most data engineering voice in a lean data org and the person who gets data science work from notebook to production. You&apos;ll own architecture and standards rather than a ticket queue. What You&apos;ll Do <ul><li>Own external market data ingestion end to end &#x2014; acquisition, normalization, and delivery into the warehouse</li><li>Own the canonical item model and the entity resolution that maps messy inbound records onto it</li><li>Build quality and monitoring that catches gaps and degradation before a stakeholder notices</li><li>Own the warehouse layer (dbt modeling, tests, documentation) and set schema contracts with product engineering so upstream changes break the build, not the metrics</li><li>Build the feature and training data layer: point-in-time correct, reproducible, and consistent between training and serving</li><li>Partner with data scientists to take models from prototype to production &#x2014; batch and real-time scoring, versioning, CI/CD, and safe rollout and rollback</li><li>Own model observability &#x2014; input drift, prediction quality, and retraining triggers &#x2014; so a degrading model gets caught by an alert, not by a bad decision</li><li>Productionize LLM-assisted pipelines where they earn their keep, with evaluation and cost controls built in</li><li>Set the engineering bar for the data org and level up DS on production-path work </li></ul>What We&apos;re Looking For <ul><li>7+ years across data engineering, ML engineering, or ML platform work with real production ownership, at senior or staff scope</li><li>Experience taming third-party data at volume &#x2014; unstable sources, schema drift, no advance notice</li><li>Entity resolution in practice, including the judgment to know when a confident match is wrong</li><li>You&apos;ve shipped ML to production alongside data scientists: built the feature pipelines, deployment path, and monitoring for models that served live decisions, not just handed off a table</li><li>Fluency in where ML breaks in the data: leakage, point-in-time joins, train/serve skew, drift</li><li>Deep SQL and Python; production dbt with tests and incremental models you actually maintained</li><li>Strong dimensional modeling &#x2014; SCD Type 2, incremental loads, backfills, late-arriving data</li><li>Cloud warehouse depth. We run BigQuery and GCP; </li><li>Comfortable with orchestration, containers, and CI/CD &#x2014; you can get a service deployed and keep it observable without being an infrastructure specialist</li><li>Clear communicator with strong ownership instincts &#x2014; you say what you&apos;ll own, what you won&apos;t, and by when</li><li>Bonus: feature store or model registry experience; LLM evaluation and cost management; pricing or valuation systems; a real interest in trading cards and collectibles </li></ul>What You&apos;ll Get In Return <ul><li>A dynamic and engaging environment focused on fostering real growth and innovation</li><li>Opportunities to create amazing products that our customers truly love and value</li><li>Comprehensive health insurance packages with dependent coverage</li><li>Competitive salary with ample opportunities for career advancement and development</li><li>Enjoy the flexibility of a fully remote work environment</li><li>401(k) plan with a 4% employer match to help you plan for the future</li><li>$100 monthly dogfooding stipend to support trying out our products firsthand</li><li>Access to employee wellness programs designed to support your overall well-being</li></ul>

Staff Data Engineer, ML Platform

Senior Data Engineer (Microsoft Fabric / Azure)Location: RemoteEmployment Type: Full-TimeAbout the OpportunityWe&apos;re partnering with an established organization undergoing a significant transformation of its enterprise data infrastructure. They&apos;re looking for an experienced Senior Data Engineer to take ownership of key data modernization initiatives, including a major migration from Azure Synapse to Microsoft Fabric.This is an excellent opportunity for a hands-on data engineer who enjoys working at the architectural level, driving technical decisions, and helping shape an organization&apos;s long-term data strategy.You&apos;ll play a key role in designing scalable data solutions, implementing governance frameworks, and mentoring junior engineers while working closely with technical leadership and business stakeholders. Key Responsibilities<ul><li>Lead key components of the organization&apos;s Azure Synapse to Microsoft Fabric migration, owning architecture, design, and implementation decisions.</li><li>Design, develop, and manage Microsoft Fabric environments, including Lakehouses, Warehouses, Notebooks, and Data Pipelines.</li><li>Establish data governance, cataloging, and architecture standards to improve data quality, consistency, and accessibility.</li><li>Develop and optimize scalable data pipelines using SQL, Python, and Azure data technologies.</li><li>Support integrations across enterprise platforms, including ERP, HRIS, financial, and asset management systems.</li><li>Collaborate with IT leadership and business stakeholders to define technical requirements and data architecture best practices.</li><li>Troubleshoot existing data pipelines and identify opportunities to improve performance and scalability.</li><li>Mentor junior data engineers and provide technical guidance on Microsoft Fabric and data migration methodologies.</li></ul> What We&apos;re Looking For<ul><li>5&#x2013;8 years of experience in data engineering, ideally with experience owning complex data platform initiatives.</li><li>Strong hands-on experience with Microsoft Fabric, including workspace architecture, Lakehouses, Warehouses, and Pipelines.</li><li>Demonstrated experience migrating workloads from Azure Synapse and Azure Data Factory to Microsoft Fabric.</li><li>Advanced proficiency in SQL and Python.</li><li>Experience designing and implementing data governance, cataloging, and data architecture frameworks.</li><li>Proven ability to lead data platform migrations from initial planning through implementation.</li><li>An applicable Microsoft Certified: Associate certification is required.</li></ul> Why Consider This Opportunity?<ul><li>Architectural Ownership: Take the lead on significant data platform modernization initiatives rather than simply executing predefined tasks.</li><li>Modern Technology: Work extensively with Microsoft Fabric, Azure, Python, and enterprise data architecture.</li><li>Technical Leadership: Influence architectural decisions and mentor other engineers.</li><li>Business Impact: Help build the foundation of a modern enterprise data ecosystem.</li><li>Established Organization: Join a long-standing business investing in the modernization of its technology infrastructure.</li></ul> Interested?If you&apos;re an experienced Data Engineer with strong Microsoft Fabric expertise and a background in enterprise data migrations, we&apos;d love to hear from you.

Location: United StatesWorkplace: RemoteEmployment Type: Full-TimeExperience: 8+ years in data engineering, ETL/ELT, and data warehousing Core Areas: Data Engineering, ETL/ELT Pipelines, Databricks, PySpark, Python, Snowflake, Healthcare Data Integration, Data Warehousing Compensation: $140,000&#x2013;$150,000 About the Role The Sr. Data Engineer, Onboarding is responsible for designing, developing, and maintaining scalable data pipelines that integrate customer healthcare data into a cloud-based analytics and operational platform. This hands-on engineering position focuses on ETL/ELT development, healthcare data ingestion, data transformation, legacy system migration, and automation that improves customer onboarding efficiency, data quality, and processing reliability. The role uses Databricks, PySpark, Python, Snowflake, and advanced SQL to process healthcare claims, remittance advice, and electronic medical record (EMR) data. Responsibilities include supporting healthcare revenue cycle management (RCM) and compliance workflows, collaborating with Implementation, Product, Support, and IT teams, resolving complex data integration issues, and mentoring junior engineers. What You&apos;ll Do <ul><li>Design, build, optimize, and maintain scalable ETL/ELT data pipelines using Databricks, PySpark, and Python, following Bronze, Silver, and Gold lakehouse architecture patterns.</li><li>Develop healthcare data ingestion and transformation workflows for X12 837I/P/D institutional, professional, and dental claims, 835 electronic remittance advice, and EMR data.</li><li>Parse, normalize, validate, and map customer healthcare datasets to the platform&apos;s data model, ensuring accurate and reliable downstream analytics and operational processing.</li><li>Design and optimize Snowflake data models, SQL transformations, and data warehousing processes to support reporting, analytics, and data accessibility.</li><li>Convert, migrate, and integrate data from legacy databases and systems, including Microsoft SQL Server, into the modern cloud data platform.</li><li>Build reusable Python, PySpark, and SQL frameworks, engineering utilities, and automated workflows that reduce manual onboarding tasks and improve processing efficiency.</li><li>Implement automated data validation, quality checks, reconciliation processes, and discrepancy resolution to maintain accuracy and data integrity.</li><li>Monitor and troubleshoot customer data feeds, ingestion pipelines, and file processing workflows after implementation, using operational metrics to identify reliability, performance, automation, and cost optimization opportunities.</li><li>Integrate and validate EMR data from systems such as Epic, Cerner, Meditech, and Athenahealth alongside claims data to enable comprehensive healthcare reporting.</li><li>Partner with Implementation, Product, Support, and IT teams to define data requirements, clarify mapping specifications, coordinate delivery priorities, and support customer onboarding.</li><li>Investigate and resolve escalated data ingestion, transformation, and integration issues through root-cause analysis and durable engineering fixes.</li><li>Track onboarding deliverables using project management platforms such as Monday.com, identify risks early, and communicate progress to internal stakeholders.</li><li>Maintain clear technical documentation covering data pipelines, transformation logic, data flows, operational procedures, and runbooks.</li><li>Coordinate the transition of completed onboarding workflows to Support teams, providing the documentation required for ongoing operations and troubleshooting.</li><li>Mentor less experienced data engineers, conduct code reviews, and share engineering practices and technical knowledge.</li><li>Maintain appropriate data security, regulatory compliance, and information integrity standards, including HIPAA requirements.</li><li>Perform additional related responsibilities as needed.</li></ul> Qualifications Required Experience <ul><li>8+ years of professional experience in data engineering, ETL/ELT pipeline development, and data warehousing.</li><li>3+ years of programming experience using Python and advanced SQL.</li><li>2+ years of hands-on experience with Databricks, including Delta Lake, notebooks, jobs, workflows, and PySpark.</li><li>Practical experience with Snowflake, including data modeling, SQL transformations, and data warehouse processes.</li><li>2+ years of experience in the healthcare industry, with a solid understanding of healthcare billing, claims processing, reimbursement models, and the revenue cycle.</li><li>Experience working with cloud infrastructure and data services on AWS or Microsoft Azure.</li><li>Experience working with SaaS applications and healthcare revenue cycle processes.</li></ul> Required Skills <ul><li>Strong technical capabilities in designing, developing, maintaining, and troubleshooting ETL/ELT pipelines and cloud-based data processing workflows.</li><li>Hands-on proficiency with Python, PySpark, Databricks, Snowflake, and advanced SQL for data ingestion, transformation, modeling, and automation.</li><li>Working knowledge of Databricks Delta Lake architecture, notebook development, scheduled jobs, and workflow orchestration.</li><li>Ability to develop and optimize SQL-based data models, warehouse transformations, and reliable data processing solutions.</li><li>Understanding of healthcare revenue cycle management (RCM), including billing processes, the claims lifecycle, and reimbursement.</li><li>Working knowledge of healthcare EDI (X12) transactions, including 837 claims and 835 remittance data used in billing and payment processing.</li><li>Ability to ingest, transform, map, and validate healthcare claims and electronic medical record data across integrated systems.</li><li>Knowledge of EMR data integration requirements and healthcare platforms such as Epic, Cerner, Meditech, and Athenahealth.</li><li>Ability to identify and resolve data quality issues through automated validation, reconciliation, monitoring, and root-cause analysis.</li><li>Understanding of data integrity, security practices, and HIPAA-related regulatory requirements.</li><li>Strong analytical, problem-solving, and troubleshooting skills with close attention to technical detail.</li><li>Effective written and verbal communication with technical and non-technical colleagues.</li><li>Collaborative working style and the ability to manage engineering responsibilities in a fast-paced environment.</li></ul> Education <ul><li>Bachelor&apos;s degree in Computer Science, Data Science, Health Informatics, Information Systems, or a related field, or equivalent professional experience.</li></ul> Preferred Qualifications <ul><li>Healthcare industry experience specifically involving revenue cycle management (RCM).</li></ul> Benefits <ul><li>Medical, dental, and vision insurance coverage.</li><li>401(k) retirement plan with company matching contributions.</li><li>Unlimited vacation policy.</li><li>Professional development, career advancement, and on-demand learning opportunities.</li><li>Peer-nominated employee awards and recognition programs.</li><li>Remote employee activities, including virtual cooking classes, yoga sessions, and mixology classes.</li></ul>

Data Engineer (Remote)

About GitHub GitHub is the world&#x2019;s leading platform for agentic software development &#x2014; powered by Copilot to build, scale, and deliver secure software. Over 180 million developers, including more than 90% of the Fortune 100 companies, use GitHub to collaborate, and more than 77,000 organisations have adopted GitHub Copilot. Locations In this role you can work from Remote, United States Overview GitHub is changing the way the world builds secure software and we want you to help change the way we secure GitHub. GitHub&#x2019;s Security Operations team detects, responds, and investigates sophisticated threat activity targeting GitHub and our users. We&apos;re looking for an experienced data engineer to help define and maintain the infrastructure, data, and policies that we rely on. In this role, you will design, build, and maintain scalable, reliable data infrastructure across Azure using technologies including Terraform, Kusto, and Airflow. You will own foundational capabilities such as data pipelines, compute clusters, tables, and data models that enable security monitoring, detection, threat hunting, incident response, and investigations. You will also help define and maintain security telemetry policy, ensuring that critical security data is available, trustworthy, appropriately governed, and useful throughout its lifecycle. This is an opportunity to join a high-impact, highly collaborative Security organization that helps drive secure outcomes for GitHub, our customers, and the broader open source software community. If you have deep experience building cloud-scale data platforms, can lead strategically across organizational boundaries, and are motivated to solve complex security data and infrastructure challenges, we want to hear from you! Responsibilities <ul><li>Design, build, and maintain secure, reliable, and scalable data infrastructure in Azure, and AWS, including Terraform-managed resources, Kusto clusters and tables, and Airflow-orchestrated ETL pipelines </li><li>Lead cross-organizational initiatives to onboard new security telemetry, and identify and close visibility gaps </li><li>Establish and advance data governance practices for security telemetry, including highly sensitive data sources </li><li>Define and drive adoption of security telemetry policies and standards, partnering with Security teams and service owners to identify and remediate gaps </li><li>Provide technical leadership to projects focused on the data platforms and infrastructure that supporting security monitoring, threat detection, hunting, investigations, and incident response </li></ul>Qualifications Required Qualifications: <ul><li>10+ years experience in security analysis, security research, cyber security, security engineering, or relevant area</li><ul><li>o OR Associate&apos;s Degree AND 9+ years experience in security analysis, security research, cyber security, security engineering, or relevant area </li><li>o OR Bachelor&apos;s Degree AND 8+ years experience in security analysis, security research, cyber security, security engineering, or relevant area </li><li>o OR Master&apos;s Degree AND 6+ years experience in security analysis, security research, cyber security, security engineering, or relevant area </li><li>o OR Doctorate AND 4+ years experience in security analysis, security research, cyber security, security engineering, or relevant area </li><li>o OR equivalent experience. </li></ul><li>5+ years of hands-on experience building and maintaining cloud scale Azure infrastructure </li><li>3+ years of deep experience with Kusto and KQL, Apache Airflow, Terraform, and Python in production environments </li><li>2+ years experience leading complex initiatives across organizational boundaries , aligning stakeholders, and translating operational requirements into durable technical solutions. </li></ul>Preferred Qualifications: <ul><li>Experience collaborating with Security Operations and Engineering teams around security telemetry requirements </li><li>Experience supporting Security Operations disciplines such as Threat Detection, Incident Response, Threat Intel, and/or Red Teaming </li><li>Experience leveraging AI workflows, where appropriate, to drive improved security outcomes </li><li>Experience designing near-real-time telemetry ingestion using Azure Event Hubs or comparable technologies </li><li>Experience establishing observability, reliability, data-quality, and cost-management practices for data platforms </li></ul>GitHub values <ul><li>Customer-obsessed</li><li>Ship to learn</li><li>Growth mindset</li><li>Own the outcome</li><li>Better together</li><li>Diverse and inclusive </li></ul>Manager fundamentals <ul><li>Model</li><li>Coach</li><li>Care </li></ul>Leadership principles <ul><li>Create clarity</li><li>Generate energy</li><li>Deliver success </li></ul>Who We Are GitHub is the world&#x2019;s leading AI-powered developer platform with 150 million developers and counting. We&#x2019;re also home to the biggest open-source community on earth (and 99% of the world&#x2019;s software has open-source code in its DNA). Many of the apps and programs you use every day are built on GitHub. Our teams are dreamers, doers, and pioneers, leading the way in AI, driving humanitarian efforts around the globe, and even sending open source to Mars (and beyond!). At GitHub, our goal is to create the space you need to do your best work. We&#x2019;re remote-first and offer competitive pay, generous learning and growth opportunities, and excellent benefits to support you, wherever you are&#x2014;because we know that people flourish when they can work on their own terms. Join us, and let&#x2019;s change the world, together. Equal Employment Opportunity GitHub is made up of people from a wide variety of backgrounds and lifestyles. We embrace diversity and invite applications from people of all walks of life. We don&apos;t discriminate against employees or applicants based on gender identity or expression, sexual orientation, race, religion, age, national origin, citizenship, disability, pregnancy status, veteran status, or any other differences. Also, if you have a disability, please let us know if there&apos;s any way we can make the interview process better for you; we&apos;re happy to accommodate!

Staff Security Data Engineer

What We Offer Join Novant Health&apos;s Enterprise Analytics team and help build scalable data solutions that drive smarter healthcare decisions. As an Advanced Analytics Engineer Senior, you will design, develop, and support enterprise data products that transform complex data into trusted, analytics-ready assets for reporting, dashboards, and advanced analytics. Schedule: 8:00AM - 5:00PM Location: Remote Department: SPX Governance Key Responsibilities <ul><li>Design, build, test, and maintain scalable data products and dimensional data models. </li><li>Develop curated datasets, data marts, and reusable analytics solutions. </li><li>Optimize data for Power BI and other reporting and analytics platforms. </li><li>Collaborate with business and technical teams to deliver high-quality data solutions. </li><li>Ensure data quality, governance, security, performance, and reliability. </li><li>Mentor junior team members and promote data engineering best practices. </li></ul>What You&apos;ll Bring <ul><li>Experience with data warehousing, dimensional modeling, and data engineering. </li><li>Strong SQL skills and experience with cloud-based data platforms. </li><li>Hands-on experience with Databricks, Unity Catalog, and Power BI preferred. </li><li>Passion for solving complex data challenges and delivering business value. </li></ul>What We&apos;re Looking For <ul><li>Education: 4 Year / Bachelors Degree, required. Bachelor&#x2019;s degree in computer science or information systems required. In lieu of a bachelor&#x2019;s degree, four (4) years of additional relevant experience, beyond the minimum experience requirement, will be considered. Graduate Degree, preferred. Master&#x2019;s degree in computer science or information systems</li><li>Experience: Minimum five years of analytics engineering, data engineering, data warehousing, analytics development, and/or business intelligence experience, required.</li><li>Additional Skills/Requirements (required):</li><ul><li>Proficiency in SQL, Python, PySpark, Spark SQL, Delta Lake, and Databricks for data transformation and analytics engineering</li><li>Strong knowledge of dimensional modeling, including facts, dimensions, conformed dimensions, bridges, aggregates, surrogate keys, slowly changing dimensions, and data grain</li><li>Experience developing curated data marts and reusable analytics assets using medallion architecture patterns</li><li>Experience building modular, maintainable transformation code for batch and incremental processing</li><li>Experience with orchestration and scheduling technologies such as Apache Airflow, Databricks Workflows, or similar tools, including dependency management and exception handling</li><li>Experience with Azure DevOps, Git, pull requests, code review, and CI/CD across development, UAT, and production</li><li>Understanding of data quality engineering, including unit testing, reconciliation, referential-integrity validation, and regression testing</li><li>Experience applying Databricks Unity Catalog, lineage, metadata, and secure access patterns to data products</li><li>Understanding of PHI/PII protection and healthcare privacy and security requirements</li><li>Ability to translate clinical, operational, and financial requirements into models, transformation rules, and acceptance criteria</li><li>Strong documentation, problem-solving, and communication skills</li></ul><li>Additional Skills/Requirements (preferred):</li><ul><li>Experience with Epic source data, including Clarity and Caboodle, and understanding of healthcare workflows and data domains</li><li>Experience supporting Power BI semantic models and DirectQuery performance</li><li>Experience with Delta Live Tables, APIs, or Azure Data Lake Storage</li><li>Experience with healthcare interoperability formats and standards such as HL7, FHIR, JSON, XML, and Parquet</li><li>Experience with dbt or comparable analytics engineering transformation and testing frameworks </li></ul></ul>Why Choose Novant Health? At Novant Health, we believe remarkable care starts with compassion for our patients, our communities, and each other. We value belonging, courage, personal growth, and teamwork, creating a space where everyone is respected, supported, and safe to show up as their full selves. Job Opening ID 196703

Advanced Analytics Engineer Senior

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

Position: Senior Data EngineerJob Location: Remote, US Job Type: Full TimeImmediate Interview Position Summary:We are looking for an experienced Senior Data Engineer to design, build, and maintain scalabledata platforms and modern data pipelines. The ideal candidate will have strong expertise in SQL,Snowflake, and DBT Cloud, along with hands-on experience across data orchestration, ingestion,governance, DevOps, and Infrastructure as Code. Basic Python skills, along with SnowPro and dbtCloud certifications are strongly preferred.The role involves working closely with data engineering, analytics, technology, and business teamsto develop reliable, scalable, and well-governed data solutions. Key Responsibilities:<ul><li>Design, develop, and maintain scalable, high-performance data pipelines and data platforms using Snowflake.</li><li>Develop efficient data transformation workflows using dbt Cloud (and dbt Core where applicable), following modular, reusable, and maintainable development practices.</li><li>Build and maintain data ingestion pipelines using dbt Cloud, working with source systems including Snowflake and PostgreSQL.</li><li>Write complex, optimized, production-grade SQL for data transformation, analysis, and processing; use basic Python scripting for automation tasks where helpful.</li><li>Implement data governance and cataloging practices using tools such as Alation and Collibra.</li><li>Follow software engineering and DevOps best practices using Git and GitHub for version control and collaboration.</li><li>Containerize applications and data workloads using Docker where required.</li><li>Develop and maintain infrastructure using Terraform and Infrastructure as Code (IaC) principles.</li><li>Implement monitoring, alerting, and operational controls using Datadog and CloudWatch.</li><li>Troubleshoot data pipeline, performance, and production issues and drive them to resolution.</li><li>Ensure pipelines are reliable, secure, and optimized for performance and cost.</li><li>Collaborate with cross-functional teams to translate business requirements into robust data engineering solutions.</li><li>Participate in code reviews, technical discussions, architecture decisions, and continuous improvement initiatives.</li><li>Mentor junior and mid-level data engineers and contribute to engineering best practices and standards.</li><li>Exposure to Workato (including Workato AI) is a plus but not required.</li></ul> Experience:<ul><li>6+ years of experience in data engineering, data platforms, or a related technology domain.</li><li>Expert-level SQL, with strong hands-on experience in PostgreSQL in addition to cloud data warehouses.</li><li>Strong practical experience with Snowflake (Databricks a plus).</li><li>Basic Python skills &#x2014; should have, for scripting and automation.</li><li>SnowPro Certification (Core or Advanced) required or strongly preferred.</li><li>DBT Cloud / dbt Certification required or strongly preferred.</li><li>Experience with modern ELT/ETL architecture and cloud-based data platforms.</li><li>Hands-on experience with orchestration tools, data ingestion platforms, and data governance frameworks.</li><li>Good understanding of CI/CD, version control, containerization, Infrastructure as Code, and monitoring/observability.</li><li>Workato experience is a nice-to-have, not a core requirement.</li><li>Strong analytical, problem-solving, and communication skills.</li></ul> Education:<ul><li>Bachelor&#x2019;s degree or master&#x2019;s in computer science, Engineering, Software Engineering or a relevant field</li></ul> About Gemini Solutions:Gemini Solutions is a global IT consulting firm specializing in banking and financial services. Founded and owned by alumni of IIT Delhi and IIIT Hyderabad, Gemini has grown from four people to more than 1,000 employees across six locations in India, the U.S., Canada, and the Middle East.Our teams bring expertise across the software development lifecycle, including application development, quality assurance, DevOps, infrastructure, and managed services. We have expertise across more than 60 technologies and have delivered globally distributed projects spanning application development, legacy-to-cloud migrations, technology transitions, capacity planning, infrastructure support, and end-to-end implementations.

Location: Arlington, VA Salary: $100,000.00 USD Annually - $160,000.00 USD Annually Description Company: Supporting the Federal Gov Positions: Mid, senior and lead Databricks openings REMOTE MUST BE US CITIZEN. MUST BE PROCESSED FOR E PUBLIC TRUST CLEARANCE Benefits: Healthcare and 401k NOTE; FOR A QUICKER RESPONSE, PLEASE APPLY DIRECT TO Ckelly@judge.com and put &#x201C;Databricks&#x201D; on the subject line. Thank you! Job Description Summary Builds and tests Databricks pipelines, transformations, migration workflows, quality controls, APIs, curated datasets, reconciliation routines, and reusable data products supporting a large federal human-capital data modernization program. What You Will Do <ul><li> Build and maintain Databricks ingestion, transformation, orchestration, migration, and data-processing pipelines.</li><li> Develop scalable ETL/ELT solutions using Databricks, Apache Spark, PySpark, Python, SQL, and Delta Lake.</li><li> Implement source-to-target mappings, transformation rules, business logic, data contracts, metadata, lineage, and data-quality requirements.</li><li> Develop migrated data feeds, APIs, curated datasets, reporting layers, and reusable data products.</li><li> Create reconciliation routines and support source-to-target validation, exception analysis, and defect resolution.</li><li> Build unit, integration, regression, performance, and data-quality tests and document technical results.</li><li> Support Git-based development, CI/CD, release management, deployment, monitoring, troubleshooting, and stabilization.</li><li> Analyze and resolve job failures, cluster-performance issues, pipeline bottlenecks, schema changes, and data-quality problems.</li><li> Collaborate with data architects, engineering leads, integration engineers, profiling analysts, testers, security specialists, governance leads, and source-system teams.</li><li> Document reusable code, technical patterns, runbooks, troubleshooting procedures, and lessons learned for later modernization waves.</li><li> Participate in Agile ceremonies, backlog refinement, sprint planning, demonstrations, and technical reviews. </li></ul>What You Will Need <ul><li> Bachelor&#x2019;s degree in computer science, data engineering, information systems, engineering, analytics, or a related field.</li><li> Minimum 4 years of experience in data engineering, software development, ETL/ELT, cloud analytics, or a related technical discipline.</li><li> Hands-on experience with Databricks, Apache Spark, PySpark, Python, SQL, Delta Lake, and workflow orchestration.</li><li> Experience building, testing, and maintaining batch data pipelines, transformations, and curated data layers.</li><li> Experience with enterprise data migration, source-to-target mapping, reconciliation, validation, and data-quality controls.</li><li> Familiarity with Git, CI/CD, automated testing, deployment, monitoring, logging, and troubleshooting.</li><li> Strong analytical, problem-solving, documentation, collaboration, and communication skills.</li><li> Ability to obtain and maintain a Federal Public Trust. </li></ul>Medical, dental, and vision insurance are available to qualified candidates who meet eligibility requirements. By providing your phone number, you consent to: (1) receive automated text messages and calls from the Judge Group, Inc. and its affiliates (collectively &quot;Judge&quot;) to such phone number regarding job opportunities, your job application, and for other related purposes. Message &amp; data rates apply and message frequency may vary. Consistent with Judge&apos;s Privacy Policy, information obtained from your consent will not be shared with third parties for marketing/promotional purposes. Reply STOP to opt out of receiving telephone calls and text messages from Judge and HELP for help. Contact: ckelly@judge.com This job and many more are available through The Judge Group. Find us on the web at www.judge.com

Databricks Data Engineer (1157916)

Job Title: Senior Data EngineerLocation: Remote Security Clearance: Active DoD Secret Clearance Omni Federal, founded in 2017 and headquartered in Washington, DC, is a highly specialized software solutions provider with a robust presence in key locations across the United States, including Boston, MA, Colorado Springs, CO, San Antonio, TX, and St. Louis, MO. Born out of the Department of Defense&apos;s software factory ecosystem, Omni has rapidly distinguished itself by delivering both mission-critical and enterprise solutions that enhance the technological capabilities of the federal government. With a focus on areas such as Command and Control, Cybersecurity, Space, Geospatial, and Modeling &amp; Simulation, Omni leverages cutting-edge commercial technology tailored to government objectives, improving mission performance and delivering transformative outcomes for the Department of Defense (DoD), Intelligence Community (IC), and their end-users. The company&apos;s innovative approach is backed by its Omni Labs and SBIR Innovation centers, where they develop advanced platforms and tools in data mesh, secure connectivity, and intelligent automation. Why Omni?<ul><li>Environment of Autonomy</li><li>Innovative Commercial Approach</li><li>People over process</li></ul> We are seeking an experienced Senior Data Engineer to support the Air Force to help in developing and operating modernized applications that are used daily by the warfighter. This is an exciting new initiative where the Air Force is mirroring Silicon Valley processes and capabilities to quickly deploy new capabilities. Candidates must be passionate, energized, and excited to work on modern architectures and solve challenging problems for our clients. Position Description (what you will do)<ul><li>Design, build, and operate streaming (Debezium change-data-capture into Amazon MSK) and batch (Apache Spark via AWS EMR) data pipelines that rapidly onboard new data sources into the program&#x2019;s Apache Iceberg-based data lakehouse, from initial ingestion through validation and production release.</li><li>Corroborate newly onboarded data against existing data lakehouse holdings to validate quality, consistency, and lineage before it is exposed to downstream consumers.</li><li>Develop and maintain the metadata, cataloging (AWS Glue as the Iceberg data catalog), and API Gateway integrations that make program data easily discoverable and consumable via Amazon Athena, Spark, and other Iceberg-compatible tools by downstream mission partners and vendors through the enterprise data mesh.</li><li>Own assigned technical tasking independently &#x2014; translate well-articulated requirements into a working solution.</li><li>Engage directly with data providers and data consumers to understand the operational context behind each data source and translate that context accurately for both technical and non-technical audiences.</li><li>Participate in an agile (Kanban/Scrum) delivery team, contributing to sprint planning, technical design discussions, and pipeline/code reviews.</li><li>Maintain pipeline and infrastructure code as Infrastructure-as-Code (Terraform) and follow established DevSecOps build and deployment pipeline processes.</li><li>Support data governance, quality, and auditability practices in accordance with Government-approved data standards for the platform.</li></ul> Requirements:<ul><li>8+ years of professional data engineering experience, including hands-on design and operation of production data pipelines.</li><li>Demonstrated experience with streaming and batch data pipeline technologies, particularly Debezium (change-data-capture), Amazon MSK (Kafka), Apache Spark (AWS EMR), and Apache Airflow.</li><li>Strong proficiency in Python and SQL, with experience integrating and validating data from multiple heterogeneous sources.</li><li>Experience with AWS data services (e.g., S3, Glue, Aurora) and containerized environments (Kubernetes), delivered through DevSecOps/CI-CD pipelines.</li><li>Demonstrated ability to work independently against well-defined tasking with minimal oversight, and to communicate effectively with both technical and non-technical stakeholders, including data providers and consumers.</li></ul> Nice to Have:<ul><li>Experience supporting DoD or Intelligence Community programs, particularly Platform One or other DoD software factory environments.</li><li>Familiarity with container security and software supply chain concepts (SBOMs, vulnerability scoring and attestation).</li><li>Experience with the Apache Iceberg table format or similar open table formats (e.g., Delta Lake, Hudi) for lakehouse architectures.</li><li>Experience with event-driven architecture (e.g., AWS EventBridge) and Infrastructure-as-Code (Terraform).</li><li>Experience designing or consuming API Gateways in an enterprise data mesh architecture.</li><li>Prior experience in a vendor- or customer-facing data steward or data liaison capacity.</li></ul> Our team is always hungry for more &#x2013; more knowledge, more problem solving, more growth, more innovation, and, ultimately, customer success. This hunger and hustle fuel our determination to excel in everything we do. It&#x2019;s not just about meeting established goals; it&#x2019;s about exceeding them. We take immense pride in applying our expertise in cutting-edge technologies and our ability to adapt to emerging trends directly to the users in the field, as our nation&#x2019;s protectors deserve nothing less. Omni Federal is an equal opportunity and affirmative action employer. Omni Federal is committed to administering all employment and personnel actions on the basis of merit and free of discrimination based on race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or status as an individual with a disability. Consistent with this commitment, we are dedicated to the employment and advancement of qualified minorities, women, individuals with disabilities, protected veterans, persons of all ethnic backgrounds and religions according to their abilities

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Scientist (Time Series Forecasting) based in Australia. Join a data-driven team developing advanced forecasting solutions that power a live energy trading platform. In this role, you will build and optimize time series models to predict weather conditions, energy market prices, and electricity grid supply and demand. Your work will directly support data-informed trading decisions by transforming analytical models into reliable, production-ready code. You will collaborate in a fully remote, distributed environment where quantitative expertise, technical excellence, and practical problem-solving are highly valued. Leveraging Python, SQL, and modern AI-powered coding tools, you will help bridge the gap between sophisticated forecasting techniques and real-world business applications. This opportunity is ideal for a hands-on data scientist who enjoys solving complex prediction challenges and delivering measurable impact in the evolving energy sector. Accountabilities <ul><li>Time Series Forecasting: Design, develop, and refine forecasting models for weather conditions, energy market prices, and electricity grid supply and demand.</li><li>Production Model Development: Translate forecasting algorithms and analytical models into robust, scalable, production-ready code that integrates with and powers a live energy trading platform.</li><li>Data Analysis &amp; Model Optimization: Analyze relevant datasets, identify patterns and trends, and improve forecasting accuracy to support reliable, data-driven trading decisions.</li><li>AI-Assisted Development: Incorporate agentic coding tools into daily development workflows to accelerate implementation, improve productivity, and support efficient software development.</li><li>Technical Integration: Work with data pipelines, analytical systems, and production environments to ensure forecasting solutions are reliable, maintainable, and suitable for operational use.</li><li>Cross-Functional Collaboration: Communicate technical findings, explain forecasting approaches, and collaborate effectively with distributed teams to align model development with business and platform requirements. </li></ul>Requirements <ul><li>Educational Background: Bachelor&apos;s degree or higher in Mathematics, Econometrics, Physics, Engineering, or another closely related quantitative discipline.</li><li>Professional Experience: At least three years of relevant professional experience in data science, quantitative analysis, forecasting, or a related field.</li><li>Time Series Forecasting Expertise: Demonstrated experience developing and applying time series forecasting models, with the ability to translate quantitative methods into practical solutions.</li><li>Programming Skills: Strong proficiency in Python and SQL for data analysis, model development, and production implementation. Experience with Go is considered an advantage.</li><li>Agentic Coding Tools: Regular, hands-on use of agentic coding tools as part of your daily development workflow, with the ability to integrate AI-assisted techniques effectively into software development.</li><li>Communication Skills: Excellent English communication skills, including the ability to explain technical concepts clearly and collaborate with stakeholders in a remote, international environment.</li><li>Analytical &amp; Problem-Solving Abilities: Strong quantitative reasoning, attention to detail, and a practical approach to addressing complex forecasting challenges and improving model performance.</li><li>Preferred Industry Knowledge: Experience working with energy markets, electricity trading, power grid data, or weather datasets is a plus. </li></ul>Benefits <ul><li>Fully Remote Work: Work remotely from anywhere in a distributed team environment.</li><li>International Collaboration: Opportunity to contribute to a global energy trading platform and collaborate with professionals across different locations.</li><li>Meaningful Technical Impact: Develop forecasting solutions that support real-world energy market decisions and operational trading activities.</li><li>Advanced Data Science Challenges: Work on practical applications of time series forecasting involving weather, market prices, and electricity supply and demand.</li><li>Modern Development Practices: Use agentic coding tools and contemporary development workflows to improve productivity and streamline model implementation.</li><li>Professional Growth: Strengthen your expertise in quantitative modeling, production-grade data science, and applied forecasting in the energy sector. </li></ul>How Jobgether Works We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role&apos;s core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. 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.

Data Scientist (Time Series Forecasting)

Full-Stack Software Engineer Location: Global, Fully Remote Job Type: Contractor | :15 hours/week Schedule: Flexible We&apos;re looking for experienced Full-Stack Software Engineers to support an AI training project focused on software development, debugging, code evaluation, and technical problem-solving. Key Responsibilities <ul><li>Develop and debug front-end and back-end applications.</li><li>Build features, APIs, services, and data models.</li><li>Understand and work across unfamiliar codebases.</li><li>Troubleshoot application, API, database, and integration issues.</li><li>Review and evaluate AI-generated code for correctness, security, performance, and maintainability.</li><li>Translate and adapt software builds between programming languages. </li></ul>Required Skills <ul><li>Python</li><li>React</li><li>JavaScript</li><li>Java</li><li>Node.js</li><li>Rust</li><li>Go</li><li>TypeScript</li><li>Strong full-stack development experience</li><li>Experience with APIs, databases, application architecture, and debugging </li></ul>Hiring Process <ul><li>Submit application and screening questions.</li><li>Complete a :30-minute AI interview.</li><li>Complete a technical assessment, if required.</li><li>Hiring manager review. </li></ul>

Sr. Full-Stack Software Engineer - Remote

Lead Product Engineer &#x2192; CTO | Python, SQL, RAG, AWS, TypeScript | AI &amp; Data Infrastructure, Start-up | Technical Ownership, 0&#x2192;1 | UK remote | Base &#xA3;80-100K + Equity The Company We&apos;re partnering with an early-stage AI company building technology that helps organisations make better decisions from complex, fast-changing information. At the heart of the business is a unique and growing data asset. They&apos;re building an intelligence layer around this data &#x2014; combining software engineering, data infrastructure, retrieval and AI to make it searchable, usable and trustworthy. Data is the product. The frontend is the wrapper. They already have customers and are now entering their next stage of growth, rebuilding the engineering team around a small number of exceptional hires. The Role &#x2013; Lead Product Engineer &#x2192; CTO | Python, SQL, RAG, AWS, TypeScript | AI &amp; Data Infrastructure, Start-up | Technical Ownership, 0&#x2192;1 | UK remote | Base &#xA3;80-100K + Equity This is a rare opportunity to join as one of the most senior technical people in the business and take significant ownership of the platform. You&apos;ll be highly hands-on across Python, data, RAG, AI and infrastructure, while helping determine what gets built, how it&apos;s built and how the engineering function evolves. You&apos;ll work directly with leadership, taking ambiguous problems and turning them into production software. As the company scales, there is potential for this person to grow into broader technology leadership and ultimately a CTO-level role. What You&apos;ll Be Doing<ul><li>Own and evolve the core AI &amp; data platform</li><li>Build backend services and APIs in Python</li><li>Design complex SQL/PostgreSQL data models</li><li>Build data pipelines and retrieval systems</li><li>Develop RAG and semantic search capabilities</li><li>Build production AI/LLM features</li><li>Make architecture and infrastructure decisions</li><li>Take ambiguous problems from 0&#x2192;1</li><li>Establish engineering standards</li><li>Help build and technically lead the engineering team</li></ul> Tech Stack - Lead Product Engineer &#x2192; CTO | Python, SQL, RAG, AWS, TypeScript | AI &amp; Data Infrastructure, Start-up | Technical Ownership, 0&#x2192;1 | UK remote | Base &#xA3;80-100K + Equity Python | SQL | PostgreSQL | TypeScript | AWS | RAG | LLMs | APIs | Data Pipelines AI is deeply embedded into how the team builds. Engineers are encouraged to use AI coding tools extensively, while remaining responsible for understanding, testing and owning what they ship. What They&apos;re Looking For<ul><li>Strong Python backend engineering</li><li>Excellent SQL / relational database knowledge</li><li>Experience with RAG, retrieval or semantic search</li><li>Experience owning production software end-to-end</li><li>Comfortable working across the full stack</li><li>Strong product and technical judgement</li><li>Comfortable solving highly ambiguous problems</li><li>Startup / scale-up experience</li><li>High ownership and autonomy</li><li>Technically strong while commercially minded</li></ul> You don&apos;t need to already be a Tech Lead. They&apos;re more interested in what you&apos;ve owned, the decisions you&apos;ve made and whether you&apos;re capable of becoming the person others rely on for technical judgement. Interview Process<ul><li>Initial conversation</li><li>Short take-home &#x2014; AI use encouraged</li><li>60-minute technical discussion</li><li>30-minute culture conversation</li></ul> Why Join? - Lead Product Engineer &#x2192; CTO | Python, SQL, RAG, AWS, TypeScript | AI &amp; Data Infrastructure, Start-up | Technical Ownership, 0&#x2192;1 | UK remote | Base &#xA3;80-100K + Equity<ul><li>Potential path from Lead Product Engineer &#x2192; CTO</li><li>Become one of the most senior technical people in the business</li><li>Genuine ownership over product and architecture</li><li>Build across AI, RAG, data and backend engineering</li><li>Work directly with company leadership</li><li>Help build the engineering team around you</li><li>Existing customers with a major new product direction</li><li>Flexible London / remote working</li><li>Equity alongside salary</li></ul> If you&apos;re a senior Product Engineer who wants more than another IC role &#x2014; and wants the opportunity to build the product, shape the technology and potentially grow into leading the entire engineering function &#x2014; we&apos;d love to hear from you. Apply with your CV and we&apos;ll be in touch if there&apos;s alignment

Lead Product Engineer → CTO | Python, SQL, RAG, AWS, TypeScript | AI & Data Infrastructure, Start-up | Technical Ownership, 0→1 | UK remote | Base £80-100K + Equity

<h3>What is <a href="https://jobicy.com/company/perfectserve" target="_blank" rel="noopener">PerfectServe</a>? </h3>
PerfectServe is a leading provider of clinical communication and physician scheduling solutions in the health IT space. The company was founded in 1997 and has grown steadily since then, with a notable jump after several major acquisitions were announced in 2019. PerfectServe now has 400+ employees, 30,000+ customers — spanning medical practices, hospitals, and health systems — and $100 million+ in annual revenue.
PerfectServe’s mission is to accelerate speed to care by optimizing provider schedules and routing communications — including messages, pages, calls, and alerts — to the right place at the right time in any care setting. By facilitating real-time information sharing, building better schedules, and automating important clinical workflows, we believe we can help our customers advance patient care and improve the well-being of their clinicians.
Leading analyst firms like Gartner® and KLAS Research have consistently validated our approach:
<ol>
<li>In 2026, PerfectServe was named highest in execution and furthest in vision in the Gartner Magic Quadrant™ for Clinical Communication and Collaboration — the clear segment leader.</li>
<li>PerfectServe also received two Best in KLAS awards in 2026 — one for physician scheduling and another for ambulatory clinical communications. That makes for 11 Best in KLAS awards over the past 9 years.</li>
</ol>
At PerfectServe, you'll have a unique opportunity to join a collaborative team with decades of experience that finds new ways to delight our customers every day. This involves consistent efforts to stay on the cutting edge of product development, which includes everything from implementing AI in new and existing solutions to brainstorming with customers about novel workflows. But you don't have to be in product to make in impact — everybody at PerfectServe contributes to important work that moves the business forward.
If you're looking for a well-established, tech-forward company full of smart people doing meaningful work, you've found the right place!
<h3>About the role</h3>
Join a new, small team building PerfectServe's data platform.
We are building the pipelines and models that bring data together from across PerfectServe's product portfolio. You will work closely with a staff data engineer and a platform engineer, with enough ownership to see your work in production and enough support to learn quickly.
The source systems are varied, so the work spans extending established pipelines and designing new ones from scratch. That range is a good part of the job.
<h3>Why this role, specifically</h3>
Joining a platform in its first months is a different experience from joining one that is five years old. The patterns are still being set, which means your questions change them. You will see the whole path — a production source system at one end, someone making a decision at the other — rather than one layer of a stack somebody else assembled.
You will have a dedicated team to work with and learn from so the ownership comes without being thrown in unsupported.
<h3>What you will do</h3>
<ul>
<li>Build and maintain ingestion pipelines from production source systems</li>
<li>Write transformation models that turn raw data into datasets people can trust</li>
<li>Apply dimensional and medallion modelling patterns as the warehouse takes shape</li>
<li>Deploy pipelines to production, and test them properly — idempotency, data quality checks</li>
<li>Contribute to data model and schema design, and to design reviews</li>
<li>Document what you build, including runbooks for the pipelines you own</li>
</ul>
<h3>What you bring</h3>
<ul>
<li>Professional experience building data pipelines, with production ownership of at least some</li>
<li>Strong SQL, and a working programming language — Python, Go or equivalent</li>
<li>Hands-on dbt, or another transformation framework</li>
<li>A cloud data warehouse — Snowflake, BigQuery, Redshift or similar</li>
<li>Practical ELT and orchestration experience (Fivetran, Airflow or equivalent)</li>
<li>Working AWS knowledge — object storage, access basics, and enough networking to reason about where data moves</li>
<li>A testing instinct for data, not only for code</li>
</ul>
<h3>Nice to have</h3>
<ul>
<li>Change-data-capture</li>
<li>SQL Server sources</li>
<li>Healthcare or another regulated data environment</li>
<li>Exposure to a BI or semantic layer</li>
</ul>
<h3>Why Join PerfectServe?</h3>
At PerfectServe, we are transforming healthcare communication and collaboration to help clinicians deliver better care. You’ll work with a dedicated and mission‑driven team in an environment that values growth, transparency, and innovation.
We offer a salary range of $115,000–$140,000 USD per year, with compensation tailored to your background, strengths, and growth potential. This range reflects our commitment to pay transparency and is based on market data, internal equity, and the scope of responsibilities. Compensation is determined by several factors, including experience, skills, and team impact. We regularly review compensation to ensure fairness and consistency. Current employees with questions are encouraged to connect with their manager or People Operations.
<h3>Benefits:</h3>
<ul>
<li>Remote first work environment</li>
<li>Health, Dental, Vision, Life and Disability Insurance options available day one.</li>
<li>401K - with match and immediately vested.</li>
<li>17 company holidays, 2 floating holidays plus competitive paid time off policy</li>
<li>Internal Advancement Opportunities</li>
</ul>
<a href="https://www.perfectserve.com/" rel="nofollow ugc noopener" target="_blank">PerfectServe</a> offers unified healthcare communication solutions to help physicians, nurses, and care team members provide exceptional patient care. PerfectServe’s cloud-based solutions enhance patient safety and reduce provider burnout by automating workflows, speeding time to treatment, optimizing shift schedules, empowering nurse mobility, and engaging patients in their own care.

Data Engineer - US Remote

<div>At <a href="https://himalayas.app/companies/livefront">Livefront</a>, we help companies design and build world-class digital products that command attention and inspire joy. We’ve helped household names like CVS, Samsung, General Mills, and Optum create experiences that have reached millions of people, and startups like HomeSpotter and Credly build entirely new businesses that challenge their industries’ status quo.</div><div>We're looking for an outstanding Senior Databricks Data Engineer to join our growing data practice — someone who builds the data and AI foundations that digital products and intelligent experiences run on. </div><div>
<div class="section page-centered">
<h3>Who you are</h3>
You are a Databricks-focused Data Engineer who understands that great data platforms are only as valuable as the products, AI workflows, and experiences they enable. You bring deep, production-grade expertise across the Databricks platform and know how to connect platform capabilities to real business outcomes.
You thrive in ambiguity and can quickly assess a client's data landscape to recommend and implement the right solutions. You understand that in consulting, your Databricks depth is most valuable when it connects platform capabilities to the products and experiences clients actually use — and you're as comfortable in a product design conversation as you are building a DLT pipeline.
You excel at translating complex data challenges into clear technical requirements and can confidently navigate conversations with everyone from data scientists to executives. Your engineering principles are mature and grounded in real-world experience across various industries and scales.
You have an interest in and a curiosity about data platforms and the latest advances in data technology.
<h3>What you will be doing</h3>
<ul>
<li>Design and build production data pipelines using Lakeflow Declarative Pipelines, Autoloader, and Structured Streaming, with end-to-end ownership of ingestion, transformation, data quality expectations, and CI/CD deployment via Declarative Automation Bundles.</li>
<li>Architect and implement Lakehouse solutions on Databricks — medallion architecture, Delta Lake, Unity Catalog — tailored to the client's analytics, AI, and application needs.</li>
<li>Build and maintain Databricks transformation layers — DLT pipelines, PySpark notebooks, and dbt — with data quality constraints and SLAs baked in.</li>
<li>Design and maintain the data and AI foundations — Unity Catalog, Feature Store, MLflow, and Model Serving — that power production ML, agent workflows, and AI-enabled digital products.</li>
<li>Collaborate with product and backend engineers to design data models, APIs, and application data contracts — ensuring the platform serves the product, not just the warehouse.</li>
<li>Consult with clients to understand their data challenges, develop data strategies, and implement sustainable solutions.</li>
<li>Adapt your approach based on project needs — sometimes leading data architecture discussions with clients, other times supporting internal teams with specialized data expertise.</li>
<li>Work within multi-cloud environments — primarily AWS and Azure — anchoring data platform recommendations around Databricks where it fits the client's architecture and goals.</li>
<li>Champion data governance through Unity Catalog — access control, lineage, data quality policies, and compliance — as a first-class part of every engagement, not an afterthought.</li>
<li>Design data-to-application architectures — including Lakebase-backed services and Databricks Apps — that connect governed data to AI workflows, digital products, and user-facing experiences.</li>
<li>Help build <a href="https://himalayas.app/companies/livefront">Livefront</a>'s Databricks practice — contributing to accelerators, internal enablement, certification goals, and Databricks partner go-to-market materials alongside delivery work.</li>
</ul>
<h3>Why you should apply</h3>
<ul>
<li>You want to work with passionate and talented people who are always looking for ways to make things better.</li>
<li>You desire a work environment where respect, mutual trust, and egoless collaboration are paramount.</li>
<li>You want colleagues who take their work seriously but not themselves, and who know how to let loose and have a good time.</li>
<li>You like being part of a team with a reputation for excellence that gives back to the community by educating, mentoring, and sponsoring.</li>
<li>You want to work on products and accounts that have outsized impact and reach.</li>
<li>You believe in sweating the details, giving a damn about quality, and taking pride in going the extra mile.</li>
<li>You want to help build a data practice specialization from the ground up — shaping how we go to market with Databricks, what we build as accelerators, and what it means to do this kind of work at a digital product company.</li>
</ul>
<h3>What you bring to the table</h3>
<ul>
<li>7-10 years of data engineering experience with at least 5 years in production Databricks environments, preferably in a consulting or client delivery context.</li>
<li>Solid working knowledge of AWS and Azure cloud services relevant to Databricks deployments — storage, networking, IAM, and compute — with GCP familiarity a plus.</li>
<li>Deep, production-grade Databricks expertise: Lakeflow Declarative Pipelines, Autoloader, Structured Streaming, Lakeflow Jobs, Unity Catalog (including fine-grained access control and lineage) — demonstrated through shipped production workloads, not prototypes.</li>
<li>Proven experience designing Lakehouse architectures — medallion patterns, Delta Lake table design, partitioning, Z-ordering, and query optimization — at production scale.</li>
<li>Hands-on experience with data pipeline testing, observability, and CI/CD for data — including unit testing, data quality frameworks, and version-controlled deployments via Git and Declarative Automation Bundles.</li>
<li>Strong proficiency in SQL and Python, with the ability to write clean, performant, and maintainable code.</li>
<li>Understanding of data modeling, schema design, and query optimization.</li>
<li>Excellent communication skills with the ability to explain complex data concepts to both technical and non-technical stakeholders.</li>
<li>Strong problem-solving skills with the ability to navigate ambiguous requirements and deliver pragmatic solutions.</li>
<li>Above-average discipline and personal organization skills.</li>
<li>Obvious comfort with critique and peer review in the context of an iterative development process.</li>
<li>A demonstrated hunger for personal and professional growth.</li>
<li>A self-evident love and care for the craft of data engineering.</li>
</ul>
<h3>Bonus points if you…</h3>
<ul>
<li>Have worked with real-time streaming technologies (Kafka, Kinesis, etc.).</li>
<li>Have hands-on experience with alternative cloud data platforms — useful context for migrations and competitive assessments, though Databricks is our primary platform focus.</li>
<li>Have experience in healthcare or fintech domains.</li>
<li>Have hands-on experience with MLOps or LLMOps on Databricks — MLflow experiment tracking, model registry, Model Serving endpoints, or Vector Search for RAG pipelines.</li>
<li>Have experience with Java, Go, or Scala.</li>
<li>Have strong illustration skills for technical diagramming and data architecture documentation.</li>
<li>Speak, write, and/or educate publicly about data engineering topics.</li>
<li>Have contributed to open-source data projects.</li>
<li>Hold or are actively pursuing a Databricks certification (Data Engineer Associate or Professional, or Apache Spark Developer) — we treat these as meaningful signals of platform depth, and they directly support our Databricks partner growth goals.</li>
<li>Have experience with Databricks Apps, or Lakebase — early familiarity with where the Databricks platform is heading is a strong differentiator.</li>
</ul>
<h3>What to expect</h3>
</div>
<div class="section page-centered">
<div>When applying, please include a short note about yourself, a summary of your work experience, and a link to any public profiles you actively maintain (e.g., GitHub, LinkedIn, etc).</div>
<div>Our hiring process moves quickly and consists of several stages for candidates who capture our attention with their initial submission, sometimes including but not limited to a short preliminary phone interview, a series of video interviews, and a short take-home exercise, which you'll have up to a week to complete.</div>
<div>Compensation is $150,000 - $180,000</div>
<h3>Additional information</h3>
<div>We go out of our way to evaluate all employees and job applicants equally based on merit, competence, and qualifications. We encourage candidates from all backgrounds to apply and consider all qualified applicants. Don't worry, every application will be reviewed by a human.</div>
</div>
</div>Originally posted on <a href="https://himalayas.app">Himalayas</a>

Senior Data Engineer (Databricks)

We&#x2019;re Changing the Rentals Industry We&#x2019;re a profitable, growth-stage company building industry-leading martech and data products for the rentals industry. While originally known for building and operating one of the U.S.&#x2019;s largest rental marketplaces - Rentable, our focus has shifted to our category-leading AI and data SaaS products with triple-digit growth rates. We&#x2019;re a fully remote team of 100+ spread across the U.S. from coast to coast. We operate on a strict no a**holes policy and are proud to have built a community of highly performing people that take our work seriously, but not ourselves. While we&#x2019;ve raised $30MM+ to date from some of the world&#x2019;s best investors, we&#x2019;re profitable with a strong balance sheet and an indefinite runway. We pride ourselves on achieving rapid growth without having to incinerate capital. If you like the idea of joining an industry-changing company made up of people who genuinely like each other, Rentable could be a great fit for you. The Role Our customers use ApartmentIQ to decide what to charge for real apartments. That number comes out of a pipeline you would own: data pulled from the property management systems that run the industry, fed through demand and renewal models, and surfaced as pricing recommendations that get acted on the same day. We&apos;re hiring a staff-level engineer to own that path end to end. It&apos;s a wide role by design - Python for the ML and ingestion services, Terraform for everything they run on, Ruby for the application layer that customers touch. Often all three in one change. If you like owning a system rather than a layer, this is that job. What You&apos;ll Be Doing <ul><li>Own a system that sets rents. Demand models, renewal probability, price elasticity, compliance scoring - you&apos;ll own the pipeline that produces them and be accountable for the recommendations landing correctly.</li><li>Solve a genuinely hard data problem. Property management systems are walled gardens with inconsistent APIs and no shared identity model. Getting clean, reconciled lease and charge data out of them is the core technical challenge of this role, and we&apos;re rebuilding it from scratch right now.</li><li>Build the infrastructure you depend on. Every database, queue, and role is in Terraform, and you&apos;ll write it. No ticket to another team to get a table provisioned.</li><li>Build the orchestration layer. Ingestion, inference, and the downstream daily jobs need to run in the right order, gate on their inputs being ready, and recover cleanly when something upstream is late. You&apos;ll own that coordination layer end-to-end &#x2014; today it&apos;s cron and careful timing; you&apos;ll make it a real pipeline.</li><li>Prove the numbers are right. Build out the observability and alerting across the data architecture &#x2014; pipeline health, data freshness, and recommendation drift &#x2014; so a bad number gets caught before a customer prices a lease against it.</li><li>Work across the whole stack, for real. Python, Terraform, and Ruby are all first-class parts of this job, not a &quot;some exposure to&quot; bullet.</li><li>Set the bar on AI-assisted engineering. A large and growing share of what we merge is AI-assisted. We want someone with strong opinions about how to do that well and the review judgment to enforce them.</li></ul> Who You Are <ul><li>You want scope, not scaffolding. You&apos;re looking for a system to own outright, and you&apos;d rather have a hard problem and autonomy than a well-defined ticket queue.</li><li>You care that it&apos;s correct. These outputs move real money. You build the checks that prove it, and you notice when a number looks wrong.</li><li>You go end to end. Empty repo to production, including the alarms, the backfill, the runbook, and the migration nobody scoped.</li><li>You raise the level around you. Your reviews make other people&apos;s code better, and work quietly moves off other plates once you&apos;re there.</li><li>You have strong opinions on AI-assisted engineering. You lean on it to ship to customers faster but you have the discipline to uphold code quality standards.</li></ul> Qualifications <ul><li>Proven Track Record: 8+ years building and operating production systems, with real ownership of something significant.</li><li>Python Depth: Strong Python in a serverless or service context - AWS Lambda, container images, dependency and runtime management, multi-stage job orchestration.</li><li>Infrastructure as Code: Hands-on Terraform. You&apos;ve stood up a production data store yourself, including the IAM, encryption, networking, and alarms around it.</li><li>Data &amp; SQL depth: Fluent in analytical SQL and data modeling - you&apos;ve built and debugged multi-stage warehouse pipelines (ours run on Redshift) and reconciled messy source data into something trustworthy. You&apos;ve worked across the major database paradigms - relational, key-value/document, and search &#x2014; and know what one is the best tool for the job at hand.</li><li>Ruby on Rails: You can own changes across a large Rails codebase, even if it&apos;s not where you&apos;ve spent the most time.</li><li>Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM.</li><li>ML in Production: You&apos;ve kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. You don&apos;t need to have trained them.</li><li>Adaptable &amp; Autonomous: Experience navigating a fast-paced, growth-stage environment where priorities shift and ownership is expected.</li></ul> Nice to Have <ul><li>Golang experience</li><li>Web scraping at scale (Playwright or similar)</li><li>OpenSearch index management and tuning</li><li>SOC 2 or similar compliance and security remediation work</li><li>xgboost, scikit-learn, or SHAP</li><li>Multifamily, PropTech, or revenue management domain experience</li></ul> Why Choose Us <ul><li>Remote-First: We offer the freedom to work from home across most of the U.S. You&#x2019;ll enjoy the flexibility of remote work, balanced with high-energy in-person offsites to build real connections and celebrate our wins together.</li><li>Competitive Compensation: We believe in hiring the best and paying accordingly. You&#x2019;ll receive a competitive salary that reflects your impact and expertise.</li><li>Paid Time Off: Take the time you need with our flexible vacation policy and dedicated paid parental leave to support you and your family&#x2019;s biggest milestones.</li><li>Your Health Matters: Stay healthy with high-quality Medical, Dental, and Vision insurance plans for you and your family.</li><li>Peace of Mind (On Us): We fully invest in your security with 100% company-paid Short-Term Disability, Long-Term Disability, and Basic Life Insurance.</li><li>Protection for Your Whole Crew: Access supplemental insurance for the unexpected, plus specialized coverage to keep your pets happy and healthy, too.</li><li>Invest in Your Future: Secure your financial goals with our 401k Program, helping you build for the long term while you help us build the company.</li></ul> If you need assistance and/or a reasonable accommodation in the application or recruiting process, please contact your recruiter. Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time. We want to alert you to potential recruiting scams targeting job seekers. Please note that our company will never request payment, personal information, or any confidential details during the interview process.

Staff Software Engineer - Data

Senior Databricks Developer - REMOTE (DC Metro Only) New Carrollton, MD 20706 Location Note: Must reside in the Washington DC Metro area Security Clearance: Active IRS MBI Required Employment Type: Full Time (W2) Position Overview Anakim Consulting is seeking an experienced Senior/Lead Databricks Developer to design, build, and optimize enterprise-grade data solutions across mission-critical programs. In this role, you will analyze complex data landscapes, prototype innovative architectures, and deliver resilient software solutions within cloud environments. This Databricks Developer role goes beyond core engineering and will help to shape technical strategy by identifying architectural gaps, introducing modern data patterns, and providing hands-on mentorship and leadership to a collaborative engineering team. Key Responsibilities <ul><li>Solution Architecture and Development: Design, develop, and deploy scalable data pipelines, analytics workloads, and software applications leveraging Databricks on AWS.</li><li>Prototyping and Analysis: Assess and interpret complex business and technical requirements, rapidly developing proof-of-concept (POC) prototypes during discovery and design phases.</li><li>Code Quality and Testing: Conduct structured peer code reviews, enforce engineering standards, write robust unit/integration tests, and execute systematic debugging, refactoring, and performance tuning across sprint cycles.</li><li>Production Support and Incident Triage: Promptly investigate, diagnose, and resolve defect reports, data anomalies, and system errors to maintain operational stability.</li><li>Architecture Modernization: Evaluate existing project architecture, identify structural gaps, and propose new frameworks or software products to enhance performance and maintainability.</li><li>Technical Leadership: Lead and mentor engineering team members through design, implementation, and delivery, fostering high engineering standards and continuous team growth.</li><li>Stakeholder Collaboration: Interface directly with client stakeholders across technical and non-technical tiers, translating mission objectives into technical roadmaps within an Agile framework.</li></ul>

Senior Databricks Developer - REMOTE (DC Metro Only)

Quick Interview || GCP Data Engineer - Remote || Full time Position - GCP Data Engineer Location &#x2013; RemotePosition Type &#x2013; FTE Harsh JainSr.Technical Recruiterharsh.jain@quantumworldit.comlinkedin.com/in/harsh-jain-a7b541b018052256693 EXT : 845 Quantum World Technologies Inc. Building No. 3, 7 Wills Way, Piscataway, New Jersey, USA 08854

gcp data engineer

Below is the complete job description Lead Data Engineer REMOTE Qualifications, Skills, and Experience <ul><li>Professional software development experience, including ownership of production systems</li><li>Proficiency in Python and experience building APIs using FastAPI or comparable frameworks</li><li>Strong SQL skills and experience working with structured data</li><li>Experience working in cloud environments, especially Microsoft Azure (Function Apps, Service Bus, AKS, etc.)</li><li>Experience with Databricks and PySpark for data-intensive applications</li><li>Experience with Domain-Driven Design and event-driven architecture</li><li>Experience with version control systems (Git, SVN)</li><li>Deep familiarity with automated testing frameworks (e.g., Pytest, Unittest)</li><li>Understanding of Agile methodologies (Scrum, XP, etc.)</li><li>Knowledge of RESTful API design and integration</li><li>Experience with performance tuning, debugging, and dependency management in production environments</li><li>Understanding of CI/CD pipelines and object-oriented design principles (e.g., SOLID)</li><li>Familiarity with front-end technologies such as Angular, React, and TypeScript is preferred</li><li>Exposure to platform engineering or self-service data tooling is a plus, especially in contexts preparing for AI-driven data applications or agentic automation frameworks</li></ul> Preferred Certifications&#xB7; Databricks certified Data Engineer Professional&#xB7; Cloud provider certifications, such as Azure Certified Solutions Architect

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