Associate Director, Data Engineering

Formation Bio is a tech and AI driven pharma company differentiated by radically more efficient drug development.

Every decision at Formation Bio, from which drug asset to pursue to how a trial is run, is only as good as the data underneath it. As the Associate Director of Data Engineering, you'll lead the team responsible for that data platform, and this role is about multiplying their impact: you're accountable for the pipelines, warehouse, and data products they build, for how fast and how well they build them, and for creating the conditions in which the engineers who build and operate them can grow, perform at a high level, and sustain that performance over time.

Responsibilities

• Hire, coach, and develop a team of data engineers, including setting goals, delivering feedback, and managing performance.
• Set the technical direction and roadmap for data engineering, prioritizing work across data quality, governance, scalability, and stakeholder experience in partnership with engineering and business leadership.
• Partner with key stakeholders such as: Data Science, Analytics, Clinical Operations, Data Managers, and Business Development on the design and delivery of pipelines and data models that support operational reporting, asset evaluation, and advanced analytics and ML use cases, ensuring your team designs solutions that close gaps and sees them through from concept to implementation.
• Oversee the architecture and maintenance of the data platform, including ingestion from clinical, operational, and third-party vendor sources, orchestration, transformation, and the Snowflake warehouse, across development, staging, and production environments.
• Ensure the team establishes and maintains strong data quality, observability, lineage, and documentation practices, and holds a high bar for engineering quality across the data platform.
• Own data governance practices for regulated and sensitive data, including access controls, auditability, and traceability appropriate for systems supporting clinical trial operations.
• Review and provide feedback on requirements and design documents for new data products and pipelines, and ensure documentation and knowledge-sharing practices stay strong across the team.
• Drive knowledge sharing, training, and mentoring on data engineering fundamentals and modern data tooling throughout the organization.
• Own the team's support rotation coverage for data platform incidents, including staffing, escalation paths, and incident retrospectives.
• Manage team budgeting, resourcing, and reporting for data engineering initiatives.

About You

• 7+ years of total experience across hands-on data engineering and people management, including 3+ years directly managing Data Engineers, Analytics Engineers, or similar.
• A track record of hiring, developing, and retaining strong engineers, with the ability to give direct, actionable feedback and set clear expectations.
• Skilled at directing a team that uses AI tools, including LLMs and agentic coding systems, as a core, daily part of how they build.
• Strong point of view on modern data stack tooling: warehousing (Snowflake), orchestration (e.g. Dagster or Airflow), transformation (e.g. dbt), and the tradeoffs between batch and streaming approaches.
• Exceptional collaboration and communication skills to effectively engage and work alongside stakeholders from diverse disciplines and varying levels of technical expertise, including Data Science, Clinical Operations, Biostatistics, BD, and non-technical partners.
• Experience managing or coordinating technical projects and programs, including resource budgeting, estimates, tracking, and reporting.
• Working knowledge of data governance, access control, and auditability practices, ideally including experience with regulated or sensitive data (clinical, PHI, or similar).
• Working knowledge of Python, SQL, Docker, GitHub, and Terraform/OpenTofu sufficient to guide and evaluate your team's technical decisions.
• Experience overseeing data quality frameworks, testing, and observability tooling for production data pipelines.
• Experience with pharmaceutical, biotechnology, or broader life-sciences industry data is a plus, but not required.

Total Compensation Range: $213,500 - $267,000