Pay
Higher than most similar jobs
$215K–$235K against $127K–$190K, the middle half of what similar US postings state.
From 2,239 postings in the last year. Stated ranges, not salaries paid.
United States - Remote
Actively hiring, first seen by us 5 hours agoPay & Benefits The pay range for this role is between $215,000 - $235,000, and will depend on your skills, qualifications, experience, and location. This role is also eligible for equity and benefits. Join our mission to revolutionize healthcare with AI.Read the full posting
Listed location: United States - RemoteRead the full posting
Employment type: Full-timeFrom the employer’s posting
Department: DataFrom the employer’s posting
Are you legally authorized to work in the United States for any employer without requiring sponsorship now or in the future?From the employer’s application form
Build and tune Databricks pipelines.
Design, build, and optimize Spark and SQL pipelines on Databricks, including incremental processing, data quality enforcement, performance tuning, and cost management.
Own the lakehouse. Architect and evolve our Databricks lakehouse, including medallion layering (bronze, silver, gold), Delta Lake, Unity Catalog governance, and workspace and compute strategy. Build and tune Databricks pipelines. Design, build, and optimize Spark and SQL pipelines on Databricks, including incremental processing, data quality enforcement, performance tuning, and cost management. Make data trustworthy. Define data contracts, quality checks, access controls, and PHI-aware governance in partnership with security and compliance.
Experience working in a highly regulated domain (Healthcare, Insurance, Finance) is required
Experience with healthcare data: claims, EHR, FHIR or HL7, and HIPAA-compliant handling of PHI.
Experience with the lakehouse stack: Spark, Delta Lake, Unity Catalog, Workflows or equivalent, and performance and cost tuning at scale.
Experience with other orchestrators (Airflow, Dagster, Prefect) and a view on when each is the right tool.
Experience building pipelines for ML or LLM applications, such as LLM-based extraction, embeddings and vector search, feature pipelines, or evaluation datasets.
Experience with cloud infrastructure (GCP, AWS, or Azure), Terraform, and Kubernetes.
Required Qualifications - Bachelors Degree in Computer Science, Electrical Engineering, Mathematics or a related field - At least 12+ years of software or data engineering experience, with a track record of designing and operating production data platforms at scale and of setting architecture across multiple teams.
Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Higher than most similar jobs
$215K–$235K against $127K–$190K, the middle half of what similar US postings state.
From 2,239 postings in the last year. Stated ranges, not salaries paid.
Day 0
Early. Similar jobs usually come down between day 6 and day 55.
From 13,214 similar postings that came down. Coming down is not always a hire.
3 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordAdd your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Experience building pipelines for ML or LLM applications, such as LLM-based extraction, embeddings and vector search, feature pipelines, or evaluation datasets. - Fluency in Python and SQL, with sound software engineering practices: testing, CI/CD, infrastructure as code, and code review. - Demonstrated practical use of agentic coding tools (such as Claude Code or similar) in real delivery work, and good judgment about when to trust, verify, and constrain them.
- Own the lakehouse. Architect and evolve our Databricks lakehouse, including medallion layering (bronze, silver, gold), Delta Lake, Unity Catalog governance, and workspace and compute strategy. - Build and tune Databricks pipelines. Design, build, and optimize Spark and SQL pipelines on Databricks, including incremental processing, data quality enforcement, performance tuning, and cost management. - Make data trustworthy. Define data contracts, quality checks, access controls, and PHI-aware governance in partnership with security and compliance.
- Experience with other orchestrators (Airflow, Dagster, Prefect) and a view on when each is the right tool. - Experience with cloud infrastructure (GCP, AWS, or Azure), Terraform, and Kubernetes. - Contributions to open-source data, workflow, or AI infrastructure projects.
Job Summary We are hiring a Senior Staff Engineer to set the technical direction for the Data Platform and to build it hands-on. Databricks is the center of the role: you will own the architecture of our lakehouse and the data pipelines, governance, and performance that run on it. In addition, you will build and run the AI pipelines that sit alongside it, using Temporal for durable orchestration. You will work across product, AI, and engineering pods, and you will raise the bar for how the whole team builds, including how we use AI coding agents to ship faster and with higher quality. You set platform-wide strategy and architecture across multiple teams. You anticipate problems a year or more out, shape the roadmap with leadership, and measurably raise engineering effectiveness across the organization, while staying close enough to the code to build the hardest parts yourself.
Key Responsibilities - Own the lakehouse. Architect and evolve our Databricks lakehouse, including medallion layering (bronze, silver, gold), Delta Lake, Unity Catalog governance, and workspace and compute strategy. - Build and tune Databricks pipelines. Design, build, and optimize Spark and SQL pipelines on Databricks, including incremental processing, data quality enforcement, performance tuning, and cost management.
- Power AI and LLM workloads. Build the data foundations for AI products: LLM-ready datasets, retrieval and vector-store pipelines, evaluation data, and the interfaces that let AI and product teams consume governed data safely. - Build AI pipelines on Temporal. In addition to Databricks, design durable workflows on Temporal for AI pipelines: scheduled and watermarked pulls from Databricks gold tables, file-ingestion workflows, and long-running LLM extraction and enrichment jobs. Establish patterns for retries, idempotency, versioning, and backfills, and keep the handoff between Databricks and Temporal clean, observable, and well governed. - Lead agentic engineering. Use AI coding agents daily and define how the team does agentic development: tooling, prompts, guardrails, code review practices, and test strategy for agent-written code.
- Experience working in a highly regulated domain (Healthcare, Insurance, Finance) is required - Deep, hands-on expertise with Databricks is highly preferred but expertise in Snowflake or Microsoft Fabric would be aligned as well. - Experience with the lakehouse stack: Spark, Delta Lake, Unity Catalog, Workflows or equivalent, and performance and cost tuning at scale.
- Experience with healthcare data: claims, EHR, FHIR or HL7, and HIPAA-compliant handling of PHI. - Databricks certifications or experience with Delta Live Tables, Lakeflow, or Databricks Asset Bundles. - Experience with other orchestrators (Airflow, Dagster, Prefect) and a view on when each is the right tool.
- Deep, hands-on expertise with Databricks is highly preferred but expertise in Snowflake or Microsoft Fabric would be aligned as well. - Experience with the lakehouse stack: Spark, Delta Lake, Unity Catalog, Workflows or equivalent, and performance and cost tuning at scale. - Experience building pipelines for ML or LLM applications, such as LLM-based extraction, embeddings and vector search, feature pipelines, or evaluation datasets.
- Databricks certifications or experience with Delta Live Tables, Lakeflow, or Databricks Asset Bundles. - Experience with other orchestrators (Airflow, Dagster, Prefect) and a view on when each is the right tool. - Experience with cloud infrastructure (GCP, AWS, or Azure), Terraform, and Kubernetes.
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New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Transform healthcare with us.
At Qualified Health, we're redefining what's possible with Generative AI in healthcare. Our infrastructure provides the guardrails for safe AI governance, healthcare-specific agent creation, and real-time algorithm monitoring, working alongside leading health systems to drive real change.
This is more than just a job. It's an opportunity to build the future of AI in healthcare, solve complex challenges, and make a lasting impact on patient care. If you're ambitious, innovative, and ready to move fast, we'd love to have you on board.
We are hiring a Senior Staff Engineer to set the technical direction for the Data Platform and to build it hands-on. Databricks is the center of the role: you will own the architecture of our lakehouse and the data pipelines, governance, and performance that run on it. In addition, you will build and run the AI pipelines that sit alongside it, using Temporal for durable orchestration. You will work across product, AI, and engineering pods, and you will raise the bar for how the whole team builds, including how we use AI coding agents to ship faster and with higher quality.
You set platform-wide strategy and architecture across multiple teams. You anticipate problems a year or more out, shape the roadmap with leadership, and measurably raise engineering effectiveness across the organization, while staying close enough to the code to build the hardest parts yourself.
Own the lakehouse. Architect and evolve our Databricks lakehouse, including medallion layering (bronze, silver, gold), Delta Lake, Unity Catalog governance, and workspace and compute strategy.
Build and tune Databricks pipelines. Design, build, and optimize Spark and SQL pipelines on Databricks, including incremental processing, data quality enforcement, performance tuning, and cost management.
Make data trustworthy. Define data contracts, quality checks, access controls, and PHI-aware governance in partnership with security and compliance.
Power AI and LLM workloads. Build the data foundations for AI products: LLM-ready datasets, retrieval and vector-store pipelines, evaluation data, and the interfaces that let AI and product teams consume governed data safely.
Build AI pipelines on Temporal. In addition to Databricks, design durable workflows on Temporal for AI pipelines: scheduled and watermarked pulls from Databricks gold tables, file-ingestion workflows, and long-running LLM extraction and enrichment jobs. Establish patterns for retries, idempotency, versioning, and backfills, and keep the handoff between Databricks and Temporal clean, observable, and well governed.
Lead agentic engineering. Use AI coding agents daily and define how the team does agentic development: tooling, prompts, guardrails, code review practices, and test strategy for agent-written code.
Set technical direction. Write and review technical designs, set platform-wide standards, and make build-versus-buy decisions that hold up over multiple years.
Multiply the team. Mentor engineers across teams, unblock other pods, and communicate trade-offs clearly to technical and non-technical stakeholders.
Bachelors Degree in Computer Science, Electrical Engineering, Mathematics or a related field
At least 12+ years of software or data engineering experience, with a track record of designing and operating production data platforms at scale and of setting architecture across multiple teams.
Experience working in a highly regulated domain (Healthcare, Insurance, Finance) is required
Deep, hands-on expertise with Databricks is highly preferred but expertise in Snowflake or Microsoft Fabric would be aligned as well.
Experience with the lakehouse stack: Spark, Delta Lake, Unity Catalog, Workflows or equivalent, and performance and cost tuning at scale.
Experience building pipelines for ML or LLM applications, such as LLM-based extraction, embeddings and vector search, feature pipelines, or evaluation datasets.
Fluency in Python and SQL, with sound software engineering practices: testing, CI/CD, infrastructure as code, and code review.
Demonstrated practical use of agentic coding tools (such as Claude Code or similar) in real delivery work, and good judgment about when to trust, verify, and constrain them.
Experience owning ambiguous, cross-team problems end to end and influencing without direct authority.
Clear written and verbal communication, including authoring design docs that others build from.
Experience with healthcare data: claims, EHR, FHIR or HL7, and HIPAA-compliant handling of PHI.
Databricks certifications or experience with Delta Live Tables, Lakeflow, or Databricks Asset Bundles.
Experience with other orchestrators (Airflow, Dagster, Prefect) and a view on when each is the right tool.
Experience with cloud infrastructure (GCP, AWS, or Azure), Terraform, and Kubernetes.
Contributions to open-source data, workflow, or AI infrastructure projects.
This is an opportunity to join a fast-growing company and a world-class team that is poised to change the healthcare industry. We are a passionate, mission-driven team building a category-defining product. We are backed by premier investors and are looking for founding team members who are excited to do the best work of their careers.
Our employees are integral to achieving our goals, so we are proud to offer competitive salaries with equity packages, robust medical/dental/vision insurance, flexible working hours, hybrid work options, and an inclusive environment that fosters creativity and innovation.
Qualified Health is an equal opportunity employer. We believe that a diverse and inclusive workplace is essential to our success, and we are committed to building a team that reflects the world we live in. We encourage applications from all qualified individuals, regardless of race, color, religion, gender, sexual orientation, gender identity or expression, age, national origin, marital status, disability, or veteran status.
The pay range for this role is between $215,000 - $235,000, and will depend on your skills, qualifications, experience, and location. This role is also eligible for equity and benefits.
Join our mission to revolutionize healthcare with AI.
To apply, please send your resume through the application below.
Selected passages from the saved posting. Check the full description for conditions and exceptions.
Pay & Benefits The pay range for this role is between $215,000 - $235,000, and will depend on your skills, qualifications, experience, and location. This role is also eligible for equity and benefits. Join our mission to revolutionize healthcare with AI.
United States - Remote
This is an opportunity to join a fast-growing company and a world-class team that is poised to change the healthcare industry. We are a passionate, mission-driven team building a category-defining product. We are backed by premier investors and are looking for founding team members who are excited to do the best work of their careers. Our employees are integral to achieving our goals, so we are proud to offer competitive salaries with equity packages, robust medical/dental/vision insurance, flexible working hours, hybrid work options, and an inclusive environment that fosters creativity and innovation. Our Commitment to Diversity
No clear work-authorization passage found. Eligibility is unconfirmed.