Data Engineer

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. Quotient Therapeutics was founded by Flagship Pioneering, an innovative enterprise that conceives, creates, resources, and grows first-in-category life sciences companies. Flagship Pioneering has created over 100 groundbreaking companies over the past twenty years, all of which are pioneering novel and proprietary biological, industrial, and engineering approaches to solve major needs in human health and sustainability. These companies include Moderna (MRNA) Generate Biomedicines, Sana Biotechnology (SANA), Tessera Therapeutics, Evelo Biosciences (EVLO), Indigo Agriculture, Seres Therapeutics (MCRB), Syros Pharmaceuticals (SYRS), and Rubius Therapeutics (RUBY). To date, Flagship has deployed over $2.5 billion in capital toward the founding and growth of its pioneering companies alongside more than $19 billion of follow-on investments from other institutions. In 2021, Flagship Pioneering was ranked 12th globally on Fortune’s “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. 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, Postg ... (truncated, view full listing at source)