H1's mission is to connect the world to the right doctor. We've built one of the largest healthcare datasets in the world: profiles of more than 10 million physicians, assembled from billions of insurance claims, 25 million publications, and nearly 500K clinical trials, with hundreds of sources feeding each doctor's profile.
85% of the top 20 pharma companies use it to decide who should run their clinical trials. Nine of the ten largest US health insurers use it to build their networks. And increasingly, the leading frontier models use our data to help patients find the right doctor. Most people we help never see our name. The engineering behind this is genuinely hard: thousands of sources, no shared identifiers, strict privacy rules, and answers that have to be right.
Data Engineering builds that dataset. The team owns the pipelines that turn raw sources into the physician profiles our customers query: hundreds of terabytes on PySpark, EMR, and Hudi. The day-to-day is deciding how the truth gets computed: which source wins when two disagree, how the same doctor gets matched across systems that have never heard of each other, and how it all stays fresh and affordable at scale. Our data is growing faster than our team, so we're hiring engineers to own the hardest pipelines end to end.
- Patient journeys: reconstruct treatment timelines from claims and health records, so customers can see how patients actually move through care and which doctors to reach.
- Performance and cost: own the hundreds-of-terabytes Spark workloads end to end, and make them faster, more reliable, and cheaper.
- Roadmap: set the technical direction for RWE data with Product, Data Science, and downstream teams, and make the architecture calls.
- Mentorship: raise the team's bar through design reviews, pairing, and deep domain teaching.
- You've designed and run Spark pipelines at scale and owned the performance, cost, and reliability tradeoffs yourself.
- Leadership: you've driven multi-quarter, cross-team technical work without formal authority.
- Stack: ours is PySpark on EMR, Hudi/Delta, Airflow, with SQL and Python everywhere. Deep in something comparable, fast ramp on the rest.
- Operations: you can deploy, debug, and un-break distributed workloads in the cloud without waiting for another team.
- Nice to have: streaming (Kafka or Kinesis); healthcare, claims, or other regulated-data experience.
Anticipated role close date: 9/15/2026
Skills Required
- 8+ years as a software, data, or backend engineer building and operating scalable, production-grade systems
- Experience with large-scale data processing or scalable distributed backend systems
- Strong proficiency in SQL, including writing and optimizing complex queries over large datasets
- Strong programming experience in Python or a modern language with ability to ramp up in Python
- Experience designing systems or large-scale datasets/pipelines with attention to performance, reliability, and maintainability
- Hands-on experience with modern engineering workflows and tooling such as Git, JIRA, and CI/CD systems
- Comfort deploying and troubleshooting distributed workloads in cloud environments
- Experience with workflow orchestration or job scheduling tools
- Demonstrated ability to independently drive complex, cross-team technical initiatives
- Experience with streaming/messaging technologies
- Background in RWE, healthcare data, or other complex/regulated data domains
- Experience using AI-assisted coding tools
What We Do
Access to medicine and healthcare is a basic human right. At H1, we believe access to the best healthcare information is also a basic human right, one that will be more important in the 21st century than ever before. Our commitment to creating a healthier future for everyone drives us to build and maintain the most current, accurate, and comprehensive healthcare knowledge base available, as well as the tools and intelligence to extract unparalleled insights to carry global healthcare forward.
Why Work With Us
We’re a team of people building products that help solve difficult problems in healthcare. We work through complex challenges every day, navigating ambiguity, wrestling with uncertainty, and pushing the boundaries of what’s possible–all while caring deeply about one another and the people we seek to help.
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