Data Engineer

Flagship Pioneering; Cambridge; On-site; GBP 50,000 - 70,000; Full time

Job summary

A biotechnology company based in Cambridge is seeking a Data Engineer to design and operate data workflows crucial for their genomics-first drug discovery platform. This mid-level position involves collaboration with biologists and data scientists, requiring strong engineering skills and experience in data management and cloud technologies. Candidates must have a relevant degree and at least three years of experience in data pipelines. A passion for biological data and a proactive mindset are essential to contribute effectively in this innovative environment.

Qualifications

• Three years or more of hands-on experience building and operating data pipelines.
• Demonstrated ability to learn local domain context.
• Familiarity with genomic and imaging data types.

Responsibilities

• Design and operate scalable data workflows.
• Collaborate with scientists to understand analytical needs.
• Ensure data quality and integrity.

Skills

Python

Linux

SQL

Collaboration

Cloud data engineering patterns

Workflow orchestration frameworks

Education

Graduate or post-graduate degree in computer science or related discipline

Tools

AWS

Dagster

Airflow

Postgres

FastAPI

Job description

Company Summary

Quotient Therapeutics, Inc. is a privately held, early‑stage company developing a novel genomics platform and therapeutics for diseases with a large unmet need.

Position Summary

We are seeking a Data Engineer to design, build, and operate data workflows and services that underpin our genomics‑first drug discovery platform. The candidate will join a collaborative Data Infrastructure team and work closely with biologists, informaticians, chemists, and data scientists to ensure that complex biological data, ranging from sequencing to histology imaging to protein structures, are reliable, accessible, and usable at scale. They bring strong engineering discipline, curiosity about biological data, and a willingness to learn domain context to truly understand user needs. This is a mid‑level role based at the Chesterford Research Campus (vicinity of Cambridge) reporting to the Head of Data Engineering. Applicants require permission to work in the UK.

Key Responsibilities

• Design, implement, and operate robust, scalable data workflows supporting genomics, imaging, and downstream analytics.
• Collaborate closely with scientists and platform stakeholders to understand analytical needs and translate them into durable data models and pipelines.
• Develop and maintain ETL/ELT workflows using modern orchestration frameworks (e.g. Dagster, Airflow, Nextflow, or similar).
• Manage large scientific data assets, including genomic sequence files and histology images, with attention to performance, cost, metadata, and lifecycle management.
• Build and operate backend data services, including databases (e.g. Athena, Postgres, or similar) and APIs (e.g. FastAPI, GraphQL, or equivalent) that expose data to scientists and applications.
• Apply best practices for version control, testing, documentation, and reproducibility across data pipelines and services.
• Ensure data quality, integrity, and traceability through validation checks, metadata standards, and monitoring.
• Continuously improve data infrastructure to reduce friction, accelerate insight generation, and support evolving scientific workflows.
• Communicate clearly and proactively with stakeholders across engineering and scientific teams.

Requirements

• Graduate or post‑graduate degree in computer science, bioinformatics, computational biology, or a related discipline, or equivalent practical experience.
• Three years or more of hands‑on experience building and operating data pipelines or data platforms in production.
• Strong collaboration skills and a pragmatic mindset suited to an interdisciplinary biotech environment.
• Demonstrated ability to learn local domain context to better serve scientific users.
• Strong proficiency in Python and Linux, with solid software engineering practices.
• Proficiency in SQL, working with backend data stores and query engines (e.g. Athena, Postgres, or similar), and exposing data via APIs.
• Experience of cloud‑based data engineering patterns (AWS preferred).
• Experience with workflow orchestration frameworks (Dagster, Airflow, Nextflow, or equivalent).
• Experience managing large data assets, including file‑based scientific data (e.g. sequencing or imaging data).
• Familiarity with common genomic, histology imaging, and/or other large scientific data types (e.g. CRAM, VCF, NDPI, OME‑TIFF) and their downstream use.
• Familiarity with modern DevOps practices, especially infrastructure‑as‑code (CDK, CloudFormation, or Terraform).

About Flagship Pioneering

Flagship Pioneering invents and builds platform companies, each with the potential for multiple products that transform human health, sustainability and beyond. Since its launch in 2000, Flagship has originated more than 100 companies. Many of these companies have addressed humanity’s most urgent challenges: vaccinating billions of people against COVID‑19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture.

Flagship has been recognized twice on Fortune Change the World list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies and has been twice named to Fast Company annual list of the World Most Innovative Companies.

Learn more about Flagship.

Recruitment & Staffing Agencies

Flagship Pioneering and its affiliated Flagship Lab companies (collectively, “FSP”) do not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to FSP or its employees is strictly prohibited unless contacted directly by Flagship Pioneering’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of FSP, and FSP will not owe any referral or other fees with respect thereto.

Equal Opportunity Statement

We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.