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)

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)

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

Lead Data Engineer

&#x26A1; Staff Data Engineer&#x1F4BC; HealthTech, Data Analytics&#x1F30D; Remote&#x1F4B0; $170,00 - $185,000 + quarterly bonus A high-growth health data organization seeks a Staff Data Engineer to lead critical ingestion and pipeline architecture focused on protected health information (PHI). This role is vital for developing and maintaining secure, reliable, and scalable data pipelines that support clinical benchmarks and performance improvement. You will work closely with leadership to design innovative solutions that ensure data integrity, privacy, and automation within a cutting-edge, AI-assisted development environment. The RoleThis role exists to own and optimize our PHI data pipelines, from ingestion to processing, ensuring compliance and operational excellence. You&#x2019;ll collaborate with technical and product teams to shape our architecture, troubleshoot complex issues, and refine our ingestion lifecycle&#x2014;empowering impactful health insights through sophisticated data engineering. Key Responsibilities:<ul><li>Design, build, and operate pipelines handling sensitive patient data using modern orchestration and cloud platforms.</li><li>Lead end-to-end ingestion processes, including validation, enrichment, masking, and audit, ensuring robustness and automation.</li><li>Implement enterprise-grade observability and data-ops automation, transforming manual tasks into automated workflows.</li><li>Collaborate with cross-functional teams and review system architecture, maintaining high standards of security and performance.</li><li>Drive innovation in data pipeline design, employing AI tools to enhance engineering efficiency.</li></ul> Requirements / Who We&#x2019;re Looking For:<ul><li>Expert Python skills in production data environments.</li><li>Strong experience with data ingestion lifecycle, validation, and failure recovery.</li><li>Proficiency with modern orchestration tools (Dagster, Airflow, or similar).</li><li>Hands-on Kubernetes deployment and operation experience.</li><li>Healthcare data literacy, including familiarity with clinical registries, EMR/EHR systems, and HIPAA compliance.</li><li>Deep SQL knowledge and experience optimizing query performance.</li><li>Authorized to work in the US without sponsorship.</li><li>Preferred: experience with patient identity resolution, cloud platforms (Azure), and data lakehouse stacks.</li></ul> Why Apply?<ul><li>Take ownership of high-impact health data systems with genuine autonomy.</li><li>Collaborate with innovative engineers and leaders shaping a vital industry.</li><li>Grow your expertise with AI-assisted development and cutting-edge cloud architecture.</li><li>Be part of a mission-driven team making a meaningful difference in healthcare quality and access.</li><li>Experience flexible, remote work empowering your best performance.</li></ul>

Staff Data Engineer

At Deckers Brands, Together, Every Step is a promise kept that every employee can bring their authentic self, is valued and supported, as a whole person, at work and beyond. Together, Every Step is how we continue to deliver exceptional business results, experience an amazing place to work, and have a positive impact on the communities and world around us. Job Title: Data Engineering Lead Reports to: Sr. Manager, Data &amp; ML Engineering Location: US (Remote) Interested applicants must reside in one of the following approved states: Arizona, California, Colorado, Indiana, Massachusetts, Minnesota, New York, Oregon, Pennsylvania, Texas, Utah, Washington The Role As the Data Engineering Lead, you will be the senior technical voice within Deckers&#x2019; data and ML engineering organization. You&#x2019;ll provide hands-on leadership for data engineering design, build quality, and delivery standards across our enterprise data products. This role is all about setting the bar for technical excellence&#x2014;establishing design patterns, coding standards, and review gates for distributed engineering teams, including external partners. You&#x2019;ll build engineering capability through design review, pairing, coaching, and structured knowledge transfer, ensuring our data products are reliable, scalable, and ready to power business decisions. We celebrate diversity--of your background, your experiences and your unique identity. We are committed to ensuring an inclusive and equitable workplace where all of our employees can Come as They Are. We believe that when we bring our different perspectives to work, we are truly Better Together. Your Impact <ul><li>Provide day-to-day technical leadership for data engineering design, build quality, and delivery standards across enterprise data products.</li><li>Review designs and enforce coding standards across internal and partner engineering, acting as the technical review gate before build begins on significant work.</li><li>Own engineering standards for model design and naming, code review, CI/CD, testing, documentation, and deployment practices across distributed teams.</li><li>Lead the design and delivery of analytics-ready data models and transformation layers using dbt, including staging, intermediate, and mart layers with tests, documentation, and governed release workflows.</li><li>Build and operate cloud-native ingestion, transformation, and delivery pipelines on AWS, focusing on reliability, performance tuning, and cost efficiency.</li><li>Establish and maintain reusable data engineering patterns for ingestion, transformation, and delivery so that solutions are repeatable.</li><li>Provide technical direction across distributed engineering teams, including external delivery partners, and hold the technical quality of their output to Deckers standards.</li><li>Coach and develop data engineers and analytics engineers through design review, pairing, technical guidance, and structured knowledge transfer.</li><li>Reduce key-person dependency by documenting engineering patterns, designs, and runbooks so that critical knowledge is retained by the organization.</li><li>Drive data quality practices within engineering, including source definitions, freshness monitoring, automated tests, reconciliation, and lineage expectations.</li><li>Lead root cause analysis and remediation for complex production data issues, strengthening patterns and controls.</li><li>Translate business needs from finance, sales, supply chain, product, and consumer stakeholders into scalable data engineering designs.</li><li>Partner with data architecture, cloud engineering, and security to align data product designs with enterprise architecture, security, privacy, and compliance requirements. </li></ul>Who You Are <ul><li>Bachelor&#x2019;s degree required, preferably in Computer Science, Computer Engineering, or a related technical field; Master&#x2019;s degree preferred.</li><li>8&#x2013;10 years of experience building enterprise-grade data platforms, pipelines, and analytics-ready data models.</li><li>3+ years providing technical leadership on data engineering delivery, including design review and standards enforcement.</li><li>Hands-on experience using dbt as a primary transformation framework in production, including model design, testing, documentation, CI/CD, and release practices.</li><li>Strong experience delivering data pipelines on AWS (e.g., S3, Redshift, Glue, Athena, Lambda) and cloud data warehouse platforms.</li><li>Experience providing technical direction to distributed engineering teams, including external delivery partners.</li><li>Experience with data quality practices including automated testing, reconciliation, freshness monitoring, and lineage.</li><li>Experience supporting machine learning and advanced analytics use cases through curated, feature-ready datasets is preferred.</li><li>Deep expertise in dimensional modeling and analytics engineering, including dbt best practices and SQL performance tuning.</li><li>Strong AWS data engineering skills including pipeline reliability, performance tuning, and cost awareness.</li><li>Ability to set and hold engineering standards across teams the role does not directly manage.</li><li>Strong design review, technical coaching, and knowledge transfer skills.</li><li>Ability to translate ambiguous business requirements into scalable and repeatable engineering designs.</li><li>Proficiency in SQL and Python, with working knowledge of orchestration tooling such as Airflow.</li><li>Familiarity with AI-assisted development workflows and their application to pipeline development, refactoring, and documentation.</li><li>Excellent problem-solving and root cause analysis skills.</li><li>Strong communication skills across technical and business stakeholders.</li><li>Comfortable working in a fast-paced, matrixed, and global environment. </li></ul>What We&apos;ll Give You &#x2013; <ul><li>Competitive Pay and Bonuses - We&#x2019;ve created a variety of competitive compensation programs to foster career development, reward success and to show our employees just how much they&#x2019;re valued.</li><li>Financial Planning and wellbeing - No matter what financial goals our employees have set, we want to help them get there. Our plans provide powerful ways to protect income, pay for expenses and invest in the future.</li><li>Time away from work - Sometimes we need time away to be with family, focus on our health or just simply recharge. Our plans support our employees&#x2019; needs to get out, get healthy and come back stronger than ever.</li><li>Extras, discounts and perks - Being a valued member of the Deckers Brands team means more than just a paycheck. From generous discounts to community-based programs, we offer a variety of cool extras</li><li>Growth and Development - Deckers Brands was built on the idea of pursuing passion. That&#x2019;s why we offer extensive opportunities and support for personal and professional development.</li><li>Health and Wellness - There&#x2019;s nothing basic about our comprehensive health and wellness programs and offerings. While at work and at play, we aim to support a healthy lifestyle. </li></ul>$122,300.00 - $165,000.00 The salary range posted reflects the estimated minimum and maximum target for new hire salaries for this role in: Goleta, California (Remote) Individual pay will be determined by location and additional factors, including job related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary for your preferred location during the hiring process. Equal Employment Opportunity Diversity and inclusion are key to our success. We are proud to be an equal opportunity employer, and our employees are people with different strengths, experiences and backgrounds who share a passion for our brands. We welcome qualified applicants regardless of their race, color, religion, sex, sexual orientation, gender identity, gender expression, national origin, age, military or veteran status, mental or physical disability, medical condition and all the other beautiful parts of your identity.

Data Engineering Lead

Hiring: AI Tech Lead | $190k&#x2013;$210k + Super | Fully Remote (Australia) I&apos;m partnering with a growing Australian software company looking for a hands-on AI Tech Lead to take technical ownership of a new AI-powered product. This is a genuinely hands-on position, with around 80% of your time spent engineering and the remainder focused on technical direction, architecture and mentoring. You&apos;ll be working within a small engineering team, with plenty of autonomy to influence how the platform is built and scaled. What you&apos;ll be working on:<ul><li>Designing and building production agentic AI workflows</li><li>Developing multi-agent orchestration and LLM-powered automation</li><li>Building reliable backend services and integrations</li><li>Implementing evaluations, monitoring and guardrails for AI systems</li><li>Making architectural decisions and mentoring engineers as the team grows</li></ul> What we&apos;re looking for:<ul><li>Strong commercial software engineering experience with TypeScript and Node.js</li><li>Hands-on experience shipping LLM-powered features into production</li><li>Experience with LangChain, LangGraph or similar orchestration frameworks</li><li>AWS experience, particularly Lambda, ECS or serverless architecture</li><li>An understanding of LLM evaluations, observability and reliability</li><li>Previous technical leadership experience without losing the hands-on element</li></ul> Package: $190k&#x2013;$210k + SuperLocation: Fully remote across AustraliaType: Permanent Australian working rights required. If you&apos;re a hands-on engineer who enjoys owning technical decisions and building AI systems that solve real problems, feel free to reach out.

Technical Lead

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

Senior Data Engineer

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

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

Senior Data Engineer, Ads

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

Senior Data Engineer II

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

Big Data Application Developer

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

Data Engineer

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

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

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

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

Database Specialist

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

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

Developer - CDI

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

Sr. Data Engineer

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

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

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

Data Engineer (Snowflake)

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

Data Engineer II

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

Data Engineer - Remote

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

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

Data Engineer - Databricks - REMOTE

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

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