Senior Scientific Data Engineer — AI-Driven Pipelines

Insilico Search Partners; Boston (MA); On-site; USD 140,000 - 200,000; Full time

Job summary

Insilico Search Partners in Cambridge, MA is seeking a Senior Scientific Data Engineer to lead the scientific data engineering practice. You will own the data layer turning fragmented instrument, lab, and manufacturing data into clean, AI-ready assets for top life sciences organizations.

This hands-on role combines architecture, mentorship, and delivery leadership, with responsibility for designing production data pipelines, implementing tests, and collaborating with product managers,

Qualifications

• 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.
• Experience leading customer-facing implementation projects across cross-functional teams.

Responsibilities

• 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

Skills

Python

SQL

Data engineering

Leadership

Cross-functional collaboration

Pre-clinical data

Visualization

Tools

React

Streamlit

Jupyter

Job description

Insilico Search Partners in Cambridge, MA is seeking a Senior Scientific Data Engineer to lead the scientific data engineering practice. You will own the data layer turning fragmented instrument, lab, and manufacturing data into clean, AI-ready assets for top life sciences organizations.

This hands-on role combines architecture, mentorship, and delivery leadership, with responsibility for designing production data pipelines, implementing tests, and collaborating with product managers,