Qualified HealthRemote
Director, Product Data Engineering
United States of America
Full Time
2 hours ago
$195,000 - $240,000 USD
H1B Sponsor Likely
Key skills
DatabricksApache SparkDelta LakeData EngineeringReusable Data FrameworksInfrastructure as CodeTerraformBicepML/LLM Pipeline DevelopmentPrompt EngineeringModel ServingEvaluation FrameworksHealthcare DataFHIREpic ClarityAzure Data FactorySnowflakePySparkPythonGitHub ActionsTeam DevelopmentAIMLGenerative AILLMAgenticETLELTSparkLeadershipProduct Management
About this role
Qualified Health is redefining what's possible with Generative AI in healthcare. The Director of Product Data Engineering will build and lead a team responsible for creating reusable data product artifacts, driving architecture decisions, and ensuring the scalability of data products.
Responsibilities:
- Build and lead a team of 4-5 data engineers focused on reusable product artifacts
- Own the product data engineering backlog in partnership with product management
- Define and enforce technical standards for notebooks, pipelines, QC modules, and documentation
- Drive the development of reusable data provisioning modules (IaC) and pipeline tooling
- Lead the build-out of data transformation and validation notebooks for agentic workflows
- Oversee initial agentic LLM call development within data pipelines — including prompt engineering, model serving patterns, and evaluation frameworks
- Own data spec documentation and ensure specs are maintained as products evolve
- Collaborate closely with Client Integration Directors to ensure product artifacts deploy cleanly into customer environments
- Develop team members technically and professionally; create a high-output engineering culture
Requirements:
- Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, or related technical field
- 8+ years in data engineering, with 3+ years in a technical leadership role
- Deep Databricks/Spark expertise at the architecture level — performance tuning, cluster management, Delta Lake design patterns
- Experience building reusable data frameworks, tooling, or platforms
- Demonstrated ability to hire, develop, and retain strong engineers
- Ability to travel for team onsites, leadership meetings or partner-facing architecture discussions 5-10% of the time
- Exposure to ML/LLM pipeline development — model serving, prompt engineering in production, evaluation frameworks
- Healthcare data experience (Epic Clarity, clinical data models, FHIR)
- IaC experience (Terraform, Bicep)
- Background building product-oriented data platforms (not just ETL/ELT pipelines)
- Prior experience at a growth-stage startup where you built a team from scratch
- Architectural Vision: Ability to see across multiple product families and design data foundations that serve all of them — not one-off solutions for each
- Product Engineering Instincts: You think about your output as a product: versioned, tested, documented, and designed for the consumer (in this case, the integration team deploying it to partners)
- Technical Depth + Leadership Range: You're comfortable operating at both the architecture whiteboard and the code review level — and you know when to toggle between them
- Influence Without Authority: You'll need to drive adoption of your team's artifacts across integration pods that have their own priorities and habits
- Builder Mentality: You're energized by creating something from nothing — building a team, establishing processes, and shipping the first version of things that don't exist yet