Lead & Scale Scientific Data Engineering for AI Platforms

TetraScience, Inc.; Cambridge; On-site; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Unlimited PTO

Health, Dental & Vision

Life Insurance

401k Savings

Disability Insurance

Equity Program

Job summary

TetraScience is seeking a hands-on Data Engineering Leader to head a team of Scientific Data Engineers in Cambridge. You will design data models, build scalable pipelines, and deliver production-grade solutions for pre-clinical data using Python, SQL, and modern tooling.

You will mentor engineers, collaborate with Product Managers and Solution Architects, drive agile delivery, ensure test coverage, and ship end-to-end data applications and dashboards with React, Streamlit, and Jupyter.

Qualifications

• 10+ years of data engineering experience or equivalent leadership track record.
• Strong Python and SQL development with scalable data pipelines.
• Experience leading projects, managing requirements, and timelines.
• Experience mentoring engineers and leading cross-functional teams.
• Experience with pre-clinical data or lab data is a plus.

Responsibilities

• Lead a team of Scientific Data Engineers and oversee data modeling and pipeline design.
• Collaborate with Product Managers, Business Analysts, and Solution Architects to capture requirements.
• Deliver production-grade data solutions with strong unit and integration tests.
• Drive Agile sprint planning, delivery milestones, and continuous process improvements.
• Build data applications and dashboards using React, Streamlit, and Jupyter.

Skills

Leadership

Python

SQL

Data Engineering

Agile

Mentorship

Cross-functional Collaboration

Tools

React

Streamlit

Jupyter Notebook

Job description

TetraScience is seeking a hands-on Data Engineering Leader to head a team of Scientific Data Engineers in Cambridge. You will design data models, build scalable pipelines, and deliver production-grade solutions for pre-clinical data using Python, SQL, and modern tooling.

You will mentor engineers, collaborate with Product Managers and Solution Architects, drive agile delivery, ensure test coverage, and ship end-to-end data applications and dashboards with React, Streamlit, and Jupyter.