At H1, we believe access to the best healthcare information is a basic human right. Our mission is to provide a platform that can optimally inform every doctor interaction globally. This promotes health equity and builds needed trust in healthcare systems. To accomplish this, our teams harness the power of data and AI-technology to unlock groundbreaking medical insights and convert those insights into action that result in optimal patient outcomes and accelerates an equitable and inclusive drug development lifecycle. Visit h1.com to learn more about us. As part of H1’s hiring process, all candidates are required to participate in an in-person final interview. Depending on your location, this may require travel. The Health Plans Software Engineering group builds the products that help health plans keep provider data accurate. It is made up of two product teams, one focused on roster automation and one focused on directory accuracy. Directory Accuracy owns the master data management and client data integration side of that work: the data platform that ingests, matches and standardizes client data to support provider directory accuracy, site feasibility, and healthcare professional credentialing. The core loop is: client entity intake, unique ID assignment, entity matching against H1's core data layer, then sync back into client feeds and pipelines. WHAT YOU'LL DO AT H1 As a Staff Software Engineer on the Health Plans team, you'll design, build, and run the big data pipelines and services behind products our health plan and life sciences customers rely on every day. We're expanding beyond pipelines into customer-facing applications and internal tools, so the data we build becomes products customers can see and use. This is a hands-on engineering role: most of your time goes to writing code in PySpark, Scala and SQL, solving hard data problems at scale, and shipping features that customers and internal teams use directly. You'll join an established team of a Staff engineer, a Senior engineer and two contractors, and report to the Director of Software Engineering, Health Plans.
Show the full description
You will
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, including its underlying schema Develop data asset management features such as scoring, status assignment and configurable intake Build the APIs and backend services that power customer-facing UIs and internal tools, making pipeline outputs easy to explore, act on and trust Contribute to customer-facing and internal applications that help bring new products to market Build self-service internal tools that let operations, customer success and other non-technical teams work with data without engineering help Work directly with messy enterprise client data, debugging issues end to end and making ingestion more reliable and repeatable Integrate clinical and provider data as new products and customers come onto the platform Work with product and design partners to shape features from customer problem through shipped product Improve pipeline performance, reliability, observability, testing and documentation Contribute to architecture decisions and design and code reviews Collaborate with adjacent teams that own feed delivery, access infrastructure, public-facing APIs and roster processing ABOUT YOU You're a senior big data engineer who loves building products, not just pipelines. You care about how data reaches the people who use it, whether that's a customer in our app or a teammate using an internal tool. You're happiest deep in the code, tuning Spark jobs, untangling messy source data and shipping features customers notice. You take ownership of systems end to end and know how to make an existing codebase better. You do well in fast-moving environments and communicate clearly with engineers, product partners and non-technical stakeholders.
REQUIREMENTS
- 8+ years of software engineering experience with a 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 that support customer-facing applications
- Working knowledge of cloud infrastructure (e.g., 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: you care about how customers use what you build
- Preferred: full-stack experience, or experience building web UIs with a modern framework (e.g., React)
- Preferred: experience building products that turn complex data into customer-facing features
- Preferred: experience building internal self-service tools
COMPENSATION
This role pays $185,000 to $230,000 per year, based on experience, in addition to equity in the form of Restricted Stock Units (RSU).
Anticipated role close date: 12/15/2026
