Data Engineer

About the role

This is a Data Engineer II (Life Sciences) opportunity with a Series C New York healthcare data company whose platform gives life sciences organisations data and AI-driven insight on doctors and trials. The role sits on the team that ingests and masters client data for large enterprise customers, with clinical trial data as a key stream. You’ll build and maintain Python and PySpark pipelines for clinical trial data intake, write transformation logic that maps raw CSV, JSON, Parquet and API data into the internal data model, tune SQL on large datasets, deliver customer-driven changes within enterprise SLAs, work with clinical subject-matter experts to turn domain knowledge into data rules, and build quality checks and observability. The ideal candidate will have 3+ years of software or data engineering experience, meaningful Python, hands-on PySpark, strong SQL on messy multi-source data and solid testing and CI/CD practice. Orchestration tools (Argo, Airflow, Databricks, dbt) and clinical trial or regulated data would be advantageous. This is a hybrid position in New York City. We're looking for someone curious, pragmatic, and eager to work across the stack with a small senior team. You'll own end-to-end delivery of major features, influence architecture, and mentor engineers.

What you'll do

• Ship customer-facing features on a weekly cadence.
• Partner with design and product on scoping and trade-offs.
• Drive technical quality through review, testing, and docs.
• Mentor one or two engineers on your team.

Requirements