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Senior Staff Engineer, Data Platform

Join Qualified Health as a Senior Staff Engineer to lead the technical direction of the Data Platform using Databricks and AI technologies.

Location
United States
Compensation
$215k–$235k/yr
Level
staff
Type
full time · Remote

Posted by employer 4 hours ago

First seen on Joblaze 3 hours ago

Last verified on the company career page 3 hours ago

Apply at Qualified Health → Save job Scanned from qualifiedhealthai.com

What you'll build

  • Own the lakehouse
  • Build and tune Databricks pipelines
  • Define data contracts and quality checks
  • Build AI pipelines on Temporal
  • Mentor engineers across teams

Must have

  • Bachelors Degree in Computer Science or related field
  • 12+ years of software or data engineering experience
  • Experience in a highly regulated domain
  • Deep expertise with Databricks
  • Fluency in Python and SQL

Nice to have

  • Experience with healthcare data
  • Databricks certifications
  • Experience with other orchestrators
  • Experience with cloud infrastructure
  • Contributions to open-source projects

Role intensity

40% coding

AI in the day-to-day

Use AI coding agents daily and define how the team does agentic development.

Requirements

Experience
12+ years
Education
Bachelor's degree

Not disclosed in this posting: visa sponsorship.

Benefits

Hybrid Work Options Equity/Stock Options Flexible Working Hours Health Insurance

Joblaze summary

In the role of Senior Staff Engineer for the Data Platform at Qualified Health, the individual will architect and build a robust Databricks lakehouse while overseeing data governance and performance. Key skills include deep expertise in Databricks, Spark, and SQL, along with experience in regulated domains like healthcare. This position is suited for seasoned engineers with a strong background in data platforms and a track record of cross-team collaboration. The role also emphasizes the use of AI coding agents to enhance development efficiency.

Joblaze insights

  • Listed today — first seen on Joblaze November 12, 2026. Last confirmed on Qualified Health's careers page November 12, 2026.
  • Salary band is above the typical range for Data Engineering roles (median ~$180,000).
  • Starts above 55% of 22 comparable staff data engineering roles in United States that list Python we track (median $212,000 across 14 companies). See Python salary trends
  • Python appears in 57.7% of 52 comparable staff data engineering roles in United States; Delta Lake appears in 3.8% of 52 comparable staff data engineering roles in United States.

Quick facts

Is the Senior Staff Engineer, Data Platform role remote?
Yes — Qualified Health lists this as a fully remote position.
What's the salary range?
Qualified Health lists $215,000–$235,000 for this role.
How much experience is required?
At least 12 years of relevant experience for this Senior Staff Engineer, Data Platform role.
What's the tech stack?
Joblaze extracted these technologies from the posting: Databricks, Delta Lake, Python, SQL, Spark, Temporal.
What seniority level is this role?
Qualified Health targets staff-level candidates for this position.
Is this full-time or contract?
Full-time for this Senior Staff Engineer, Data Platform role at Qualified Health.

From the original posting

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.

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.

  • 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.

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.

  • 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.

Desirable Qualifications

  • 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.

Why Join Qualified Health?

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.

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.

To apply, please send your resume through the application below.

 

Standard company text repeated across Qualified Health's postings is omitted here.

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