Data Engineer (Life Sciences)

Join H1, a leading company in the life sciences industry, as a Data Engineer II. In this role, you will build and operate the pipelines behind H1's clinical trials data, working primarily in Python, PySpark, and SQL. You will collaborate with clinical subject matter experts and Customer Success Managers to turn their domain knowledge into pipeline logic that holds up in production. You will also be responsible for writing and tuning SQL against large datasets, developing transformation logic, and building data quality checks. This position offers flexible work hours, commuter benefits, stock options, and unlimited PTO.

• Construire et maintenir des pipelines de données en Python et PySpark pour les flux de travail d'entrée de données des essais cliniques.
• Développer la logique de transformation qui mappe les données brutes des essais et des clients aux modèles de données internes de H1.
• Participer aux revues de code, maintenir un haut niveau de qualité et d'adhérence aux normes d'ingénierie.

• 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
• Working in an operationally-driven environment where reliability and on-time delivery matter as much as new feature work
• 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
• Working with PySpark or a comparable distributed processing framework on datasets too large for a single machine
• Building and shipping production data pipelines in Python, with an understanding of what makes them reliable and maintainable under real load
• 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
• Writing SQL well enough to answer hard questions about data, not just retrieve it
• Familiarity with clinical trial data, healthcare data, or another regulated data domain a plus
• Experience working with cross-functional and non-technical stakeholders
• Familiarity with entity matching or data mastering a plus
• Demonstrated experience building and maintaining production-grade data pipelines in Python
• Hands-on experience with PySpark or a similar distributed data processing framework
• 3+ years of experience in software or data engineering, with meaningful Python in your background
• Familiarity with AWS services (S3, Lambda, ECS, or similar) a plus
• Experience with pipeline orchestration tooling (Argo, Airflow, Databricks, dbt, or similar) preferred
• Strong SQL skills, including working with large, messy, multi-source datasets
• Strong understanding of software quality practices: testing, code review, documentation, and CI/CD