Senior Data Engineer
Formation Bio2 months ago
Responsibilities
- Design and operate production ingestion systems for clinical, operational, and third-party vendor data.
- Own shared data models, data contracts, transformations, orchestration, warehouse models, and downstream interfaces.
- Partner with Product Engineering on application data models, source-system contracts, APIs, events, and data access patterns.
- Partner with Data Science on productionized training datasets, feature pipelines, data interfaces, and ML use cases.
- Build versioned, tested, observable, and maintainable pipelines for data cleaning, normalization, and transformation.
- Create semantically clear, discoverable, machine-readable, permission-aware, traceable, and safe-to-query data products.
- Establish data quality, testing, freshness, completeness, lineage, documentation, observability, and governance practices.
- Support incident response for data platform issues and contribute to architecture reviews, mentoring, and engineering practice improvements.
- Use AI tools, including LLMs and agentic coding systems, to accelerate development while validating their output.
Requirements
- 5+ years of relevant data engineering experience building and operating production data systems.
- Required experience with pharmaceutical, biology, HIPPA, or other regulated data core to biotech.
- Strong Python and SQL skills with deep experience in data modeling and warehouse systems, especially Snowflake.
- Experience with Dagster or equivalent orchestration and transformation tooling such as dbt.
- Experience with data contracts, schema evolution, data quality testing, observability, lineage, and production incident response.
- Experience integrating complex clinical, operational, vendor, or other messy source data.
- Working knowledge of Docker, GitHub, and Terraform or OpenTofu sufficient to partner with SRE.
- Experience building data products and access patterns for applications, Data Science, analytics, human users, and AI-enabled employees and agents.
- Strong judgment about reusable platform capabilities versus one-off stakeholder solutions and fluency with validating AI-generated code and data-modeling decisions.
- Exceptional collaboration and communication skills across technical and non-technical partner teams.
- Experience building validated computerized systems (CSV) is a plus.
Benefits
- Base salary, equity, comprehensive benefits, and generous perks are offered; compensation figures are excluded here because the posting labels the range as total compensation.
- Hybrid work requires 3 days per week in the office.
- Hiring is prioritized in the New York City and Boston metro areas; Research Triangle, NC and San Francisco Bay Area applicants may also be considered, with relocation required if applicable.
About Formation Bio
Formation Bio builds AI-driven technology platforms and runs a pharmaceutical development business that designs and executes clinical trials for in-licensed or acquired drugs. It partners with pharma, biotechs, and research groups to take clinical-stage assets through proof of concept and beyond, aiming to reduce trial time and improve data quality. The privately held company is headquartered in New York and originated as TrialSpark before rebranding to Formation Bio.