Data Engineer (Life Sciences)

- 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…