Senior Data Engineer - Real World Data

Formation Bio is seeking a Senior Data Engineer to join the Scientific Data Intelligence (SDI) team. The successful candidate will help transform Real World Data (RWD) into structured, analytics-ready assets.

Responsibilities:

• Model and transform raw EHR and claims data into clean, canonical, and analytics-ready datasets using SQL, Python, and clinical standards like OMOP.
• Build and manage scalable data pipelines using Dagster for orchestration, dbt for transformation, and Snowflake as the primary compute and storage engine.
• Conduct hands-on RWD analyses to answer scientific and strategic research questions.
• Partner with Data Scientists and clinical leads to design and execute observational studies.
• Implement data validation, completeness, and observability frameworks.
• Apply Generative AI techniques within transformation and analysis layers.
• Communicate findings clearly to both technical and non-technical stakeholders.

Requirements:

• 5+ years of experience in data engineering, ideally with at least 2 years working in healthcare or life sciences.
• Experience with ontologies and biomedical schemas (e.g. UMLS, LOINC, ICD9/10, MeSH).
• Fluency in SQL and Python, and experience building and maintaining production-grade pipelines.
• Experience building longitudinal patient cohorts from EHR or claims data.
• Solid understanding of causal inference frameworks.
• Working familiarity with real-world evidence study design concepts.
• Hands-on expertise with modern data infrastructure, such as Snowflake, dbt, and Dagster.

Total Compensation Range: $204,500 - $267,000