Qualified Health - Director, Product Data Engineering
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Requirements
• Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, or related technical field • Bachelor's degree • 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 • Ability to travel • 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 • Architectural Vision: • 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) • Product Engineering Instincts: • 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 • Technical Depth + Leadership Range: • Influence Without Authority: You'll need to drive adoption of your team's artifacts across integration pods that have their own priorities and habits • Influence Without Authority: • 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 • Technical Environment: • Our data infrastructure is built on modern cloud technologies including: • Azure Databricks + Data Factory (plus Fabric and Snowflake integrations) • Azure Databricks + Data Factory • PySpark for distributed data processing • PySpark • GitHub Actions + Terraform for CI/CD and Infrastructure as Code • GitHub Actions + Terraform • Python with type-safe patterns and modern frameworks • Python • Healthcare data formats including FHIR, Epic Clarity, and other EHR schemas
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
Benefits
• 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 that is 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
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