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Salary: USD 185,000 - 230,000 / annual
H1 is a healthcare data and AI platform on a mission to provide optimal medical insights globally and promote health equity. The Health Plans Software Engineering group builds products that help health plans maintain accurate provider data. The Directory Accuracy team owns the master data management and client data integration platform that ingests, matches, and standardizes client data to support provider directory accuracy, site feasibility, and healthcare professional credentialing.
As a Staff Software Engineer on the Health Plans team, you will design, build, and operate large-scale data pipelines and services that health plan and life sciences customers rely on daily. This is a hands-on role focused on writing code in PySpark, Scala, and SQL while solving hard data problems at scale. You'll work on expanding beyond pipelines into customer-facing applications and internal tools.
Key responsibilities include:
- Design, build, and operate large-scale data pipelines for ingesting, transforming, matching, and syncing client data using PySpark, Scala, and SQL
- Build and improve the entity matching service that resolves client records against H1's core data layer
- Develop data asset management features such as scoring, status assignment, and configurable intake
- Build APIs and backend services powering customer-facing UIs and internal tools
- Contribute to customer-facing and internal applications bringing new products to market
- Build self-service internal tools enabling non-technical teams to work with data independently
- Work directly with messy enterprise client data, debugging issues end-to-end and improving ingestion reliability
- Integrate clinical and provider data as new products and customers join the platform
- Collaborate with product and design partners to shape features from problem through shipped product
- Improve pipeline performance, reliability, observability, testing, and documentation
- Contribute to architecture decisions and participate in design and code reviews
- Collaborate with adjacent teams owning feed delivery, access infrastructure, public-facing APIs, and roster processing
You are a senior big data engineer who loves building products, not just pipelines. You care deeply about how data reaches end users—whether customers in the app or teammates using internal tools. You thrive deep in code, tuning Spark jobs, untangling messy source data, and shipping features customers notice. You take end-to-end ownership of systems and know how to improve existing codebases. You communicate clearly with engineers, product partners, and non-technical stakeholders in fast-moving environments.
REQUIREMENTS:
- 8+ years of software engineering experience with strong focus on data engineering and building data-driven products
- Deep experience designing, building, and running production big data pipelines at scale (ETL/ELT, orchestration, scheduling, monitoring)
- Strong proficiency in PySpark, Scala, Python, and SQL
- Solid experience with distributed data processing and performance tuning in Spark
- Experience building APIs or backend services supporting customer-facing applications
- Working knowledge of cloud infrastructure (AWS, GCP, or Azure)
- Hands-on experience with entity resolution, record matching, or master data management
- Experience with data quality, scoring, or validation frameworks
- Comfort working directly with client data, including messy source files and onboarding enterprise customers
- Product-engineering mindset: care about how customers use what you build
- Preferred: full-stack experience or experience building web UIs with modern frameworks (e.g., React)
- Preferred: experience building products that turn complex data into customer-facing features
- Preferred: experience building internal self-service tools
- Preferred: experience with healthcare data such as provider or HCP directories, rosters, credentialing, clinical trial or site feasibility data
- Preferred: experience with CTMS or other clinical systems data
