Associate Director, Data Engineering

About the Position

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.

This is an AI-native engineering organization, and for this team that means building the data platform itself in an AI-native way. We expect you and your team to be fluent, fast, and always pushing the edge of what modern AI tools, including agentic coding systems, can do as a core part of how the team builds pipelines, models data, investigates data quality issues, and improves engineering workflows. You should coach your team to treat AI as a permanent force multiplier, not a novelty, while instilling the judgment needed to validate its output and operate trustworthy data systems, especially where clinical and regulated data are involved.

In this role, you will lead a team of data engineers and evolve an established data platform for Formation Bio's next stage of growth. You will clarify ownership, separate concerns where needed, strengthen reliability and governance, and increase the speed at which trusted data supports clinical operations, asset evaluation, and company decision-making. Partnering closely with Data Science, Analytics, Clinical Operations, Biostatistics, and Business Development, you will set technical direction and priorities, unblock your team, represent data engineering needs in cross-functional planning, and promote a culture of trusted, well-governed data throughout the company.

This position is ideal for a manager who leads from the front: someone who is passionate about developing engineers, sets a high bar for pace and rigor, and builds a team that makes it easy and fast for the rest of the company to find, trust, and use data. Your experience with engineering management, technical leadership, and data platform architecture will be instrumental in driving Formation Bio's mission to bring new treatments to patients faster and more efficiently.

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. We're looking for someone who has built and managed these systems and brings that depth to how they lead.
• 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. Able to set a high bar for using AI responsibly to accelerate pipeline development, investigate data quality issues, improve data modeling workflows, and increase the team's overall engineering leverage.
• 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