Senior Data Engineer: Biotech Data Platform & AI

Formation Bio; San Francisco (CA); Hybrid; USD 186,000 - 232,000; Full time

Job summary

Formation Bio seeks a Senior Data Engineer to build trusted data systems across clinical operations, asset evaluation, and analytics, enabling AI-enabled employees and agents. You will design ingestion pipelines across clinical, operational, and vendor data while shaping data models and production data products.

You will collaborate with Product Engineering, Data Science, and other partners to ensure data quality, governance, and scalable data access for applications and ML use cases.

Qualifications

• 5+ years of data engineering experience building production data systems.
• Experience with pharmaceutical, biology, HIPAA or other regulated data core to biotech is required.
• Strong Python and SQL skills, with deep experience in data modeling and warehouse systems, especially Snowflake.
• Experience with Dagster as an orchestration system (or equivalent) transformation tooling such as dbt or an equivalent approach.
• Experience with data contracts, schema evolution, data quality testing, observability, lineage, and production incident response.
• Experience integrating messy clinical, operational, vendor, or otherwise complex source data.
• Working knowledge of Docker, GitHub, and Terraform or OpenTofu sufficient to partner effectively 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 when to build reusable platform capabilities versus one-off stakeholder solutions.
• Daily fluency with AI tools and the ability to validate generated code, transformations, and data-modeling decisions.
• Exceptional collaboration and communication skills across Product Engineering, Data Science, Clinical Operations, Data Management, Business Development, and other non-technical partners.
• Experience working within and building validated computerized systems (CSV) is a plus.

Responsibilities

• Design and operate production data systems that ingest clinical, operational, and third-party vendor data into reliable, queryable data products.
• Own shared and canonical 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.
• Turn recurring data cleaning, normalization, and transformation work into versioned, tested, observable, and maintainable production pipelines.
• Build data products for clinical operations, asset evaluation, Business Development, analytics, machine learning, and AI Enabled Employees and Agents.
• Design data products that are semantically clear, discoverable, machine-readable, permission-aware, traceable, and safe to query.
• Establish strong data quality, testing, freshness, completeness, lineage, documentation, and observability practices.
• Own data governance practices for sensitive and regulated data, including access controls, auditability, traceability, and appropriate data handling.
• Participate in support and incident response for data platform issues, including diagnosis, stakeholder communication, remediation, and prevention of recurrence.
• Use AI tools, including LLMs and agentic coding systems, to accelerate pipeline development, data modeling, debugging, documentation, and data quality investigation while validating their output.
• Contribute to architecture and design reviews, mentor other engineers, and improve the engineering practices used across the organization.

Skills

Python

SQL

Snowflake

Data modeling

Dagster

dbt

Data pipelines

Data governance

Terraform

GitHub

Tools

Docker

GitHub

Terraform

OpenTofu

dbt

Job description

Formation Bio seeks a Senior Data Engineer to build trusted data systems across clinical operations, asset evaluation, and analytics, enabling AI-enabled employees and agents. You will design ingestion pipelines across clinical, operational, and vendor data while shaping data models and production data products.

You will collaborate with Product Engineering, Data Science, and other partners to ensure data quality, governance, and scalable data access for applications and ML use cases.