Data Engineer, H1
Life Sciences
$110-135k
+ stock options
Platform connecting healthcare professionals
Be an early applicant
Platform connecting healthcare professionals
501-1000 employees
Be an early applicant
$110-135k
+ stock options
501-1000 employees
Company mission
To create a healthier future by delivering a platform that connects stakeholders across the healthcare ecosystem and encourages purposeful relationships.
Role
Who you are
- You are a data engineer with a strong Python foundation and real distributed-processing experience. You're drawn to high-impact teams where the work is tangible: pipelines running, enterprise customers getting their data on time, clinical data that people make real decisions from
- You're comfortable in an environment where recurring production runs and customer SLAs shape day-to-day priorities, and where a customer request can reorder your week. You'd rather sit down with a domain expert and understand why the data looks the way it does than build to a spec handed to you secondhand
- Building and shipping production data pipelines in Python, with an understanding of what makes them reliable and maintainable under real load
- Working with PySpark or a comparable distributed processing framework on datasets too large for a single machine
- Writing SQL well enough to answer hard questions about data, not just retrieve it
- Working in an operationally-driven environment where reliability and on-time delivery matter as much as new feature work
- Working directly with non-engineering partners, subject matter experts, analysts, or customer-facing teams, and communicating clearly about data with people who don't read code
- Holding a high bar in code review and expecting the same from those who review your work
- Identifying data problems early and seeing work through to resolution rather than handing it off
- 3+ years of experience in software or data engineering, with meaningful Python in your background
- Demonstrated experience building and maintaining production-grade data pipelines in Python
- Hands-on experience with PySpark or a similar distributed data processing framework
- Strong SQL skills, including working with large, messy, multi-source datasets
- Strong understanding of software quality practices: testing, code review, documentation, and CI/CD
- Experience working with cross-functional and non-technical stakeholders
- Experience with pipeline orchestration tooling (Argo, Airflow, Databricks, dbt, or similar) preferred
- Familiarity with clinical trial data, healthcare data, or another regulated data domain a plus
- Familiarity with entity matching or data mastering a plus
- Familiarity with AWS services (S3, Lambda, ECS, or similar) a plus
What the job involves
- As a Data Engineer II on the H1DN team, you will build and operate the pipelines behind H1's clinical trials data. You'll work primarily in Python, PySpark, and SQL, and you'll work directly with clinical subject matter experts and Customer Success Managers to turn their domain knowledge into pipeline logic that holds up in production
- Build and maintain the Python and PySpark pipelines behind the CTMS trial data pipeline intake workflows, including scoring and status logic
- Develop the transformation logic that maps raw trial and customer data to H1's internal data models, handling diverse source formats including CSV, JSON, Parquet, and APIs
- Write and tune SQL against large datasets to investigate data questions, validate pipeline output, and support analysis that clinical SMEs and customer-facing teams depend on
- Turn around customer-driven changes quickly, scoping requests as they arrive, shipping changes that hold up under enterprise SLAs, and reworking logic as customer needs shift mid-flight
- Partner with clinical SMEs to translate domain expertise into concrete data rules, then walk them through the results, explain what the pipeline did and why, and fold their feedback back into the logic
- Build the data quality checks, validation logic, and reconciliation that let non-engineers trust pipeline output without reading the code
- Participate in code reviews, maintaining a high bar for quality and adherence to engineering standards
- Monitor and improve pipeline observability, contributing to alerting and dashboards that surface job health and data anomalies for both the team and internal users
Application process
- Anticipated role close date: 10/20/2026
Our take
The increasing costs and difficulty of drug discovery requires healthcare organizations and pharmaceutical companies to be able to quickly connect to professionals and thought leaders with specific credentials or research history. H1 addresses these needs by allowing life sciences companies, hospitals and healthcare systems to locate the professionals they need.
H1 is the world’s largest healthcare database. It acts a bit like LinkedIn for healthcare professionals, and has already built a network of more than 9 million users. It has also built a corporate client base of 250 enterprises which is able to access its data which spans more than 250 million patients and over 10 billion health care claims.
The company graduated from Y Combinator's accelerator program in January 2020, and has since raised considerable funding, expanded into Europe and Asia, and built out its data network. It continues to attract investment, most lately from CVS Health Ventures, which showcases the industry regard for its offering.
Freddie
Company Specialist at Welcome to the Jungle
Insights
-7% employee growth in 12 months
Company
Funding (last 2 of 6 rounds)
May 2026
$40m
LATE VC
Jun 2022
$23m
SERIES C
Total funding: $227.2m
Company benefits
- Flexible work hours
- Commuter benefits
- Stock options
- Computer setup
- Work from home opportunities
- Health & life insurance
- Retirement options
- Unlimited PTO
- Flex Give & Flex Spend
- Impactful BRGs
Company HQ
Flatiron District, New York, NY
Leadership
Ariel Katz
(CEO & Co-Founder)Previously founded acquired online database, ResearchConnection, before co-founding H1.
Ian Sax
(Co-Founder)Ian has been building businesses for over two decades. He began his start up career at The Carson Group, where he built the firm's global people, institution, and shareholder platform.
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