01Overview
About the job
Senior/Staff Scientific Data Engineer
Location: Cambridge, MA - Onsite 3 days a week
Type: Full-time
A well-funded scientific data and AI company is hiring a Senior Scientific Data Engineer to lead its scientific data engineering practice.
You will own the data engineering layer that turns fragmented instrument, lab, and manufacturing data into clean, usable, AI-ready assets for the world's leading life sciences organizations. This is a hands-on senior role with real technical authority: you will architect solutions, lead design sessions, set the quality bar, and mentor a growing team of data engineers.
If you have spent your career building data products and want that work pointed at drug discovery, development, and manufacturing, this is that job.
What You'll Do
Build schemas, parsers, and integration solutions for pre-clinical scientific data from R&D lab instruments, manufacturing systems, CROs, CDMOs, ELNs, and LIMS — including messy vendor formats like .raw, .fid, .xlsx, .pdf, and proprietary binaries
Use AI agents to accelerate schema and parser development, then extract the reusable components into productized Python libraries
Design and build production data pipelines with full unit and integration test coverage
Build data applications, reports, and dashboards in React, Streamlit, and Jupyter
Partner with product managers, solution architects, business analysts, and ML engineers to translate customer requirements into shipped solutions
What You Bring
8+ years building data products as a data engineer or in a closely related role
8+ years of Python and SQL in a data-focused capacity
Track record leading projects: owning requirements, timelines, and delivery milestones
Experience running multiple customer-facing implementation projects across cross-functional teams
Hands-on experience with pre-clinical or lab data, and working directly with scientists
Dashboarding and visualization experience with React and/or Streamlit
Why This Role
Genuine technical ownership — you set the architecture, not just implement it
Work at the front of the AI-native data curve, with agent-assisted engineering as part of the daily toolkit
Direct line of sight from your pipelines to research that reaches patients
Strong partner ecosystem and a company operating at real scale in life sciences
