Senior Data Engineer II - Electronic Health Records (EHR)

About Formation Bio

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

Advancements in AI and drug discovery are creating more candidate drugs than the industry can progress because of the high cost and time of clinical trials. Recognizing that this development bottleneck may ultimately limit the number of new medicines that can reach patients, Formation Bio, founded in 2016 as TrialSpark Inc., has built technology platforms, processes, and capabilities to accelerate all aspects of drug development and clinical trials. Formation Bio partners, acquires, or in-licenses drugs from pharma companies, research organizations, and biotechs to develop programs past clinical proof of concept and beyond, ultimately helping to bring new medicines to patients. The company is backed by investors across pharma and tech, including a16z, Sequoia, Sanofi, Thrive Capital, Sam Altman, John Doerr, Spark Capital, SV Angel Growth, and others.

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At Formation Bio, our values are the driving force behind our mission to revolutionize the pharma industry. Every team and individual at the company shares these same values, and every team and individual plays a key part in our mission to bring new treatments to patients faster and more efficiently.

About the Position

We’re looking for a Senior Data Engineer to join the Data Platform team at Formation Bio to help transform Electronic Health Records (EHR) data into structured, analytics-ready assets. In this role, you’ll be partnering closely with our Data Science team to model, transform, and refine data for operational and scientific use cases.

This position sits at the intersection of healthcare data engineering, modern data platform infrastructure, and generative AI. While your initial focus will be on building high-quality EHR models for Formation Bio platform, you’ll also contribute to our broader data architecture by leveraging tools like Snowflake, Dagster, and dbt to enable scalable, governed, and high-reliability pipelines.

The ideal candidate combines deep data engineering experience with both GenAI fluency (e.g., LLM-based entity extraction, summarization, classification) and strong technical expertise with modern data tooling. You’ll play a key role in shaping how healthcare data becomes discoverable, structured, and impactful across the organization.

Responsibilities

• Model and transform raw EHR data into clean, canonical, and analytics-ready datasets using SQL, Python, and clinical standards like FHIR, HL7, or OMOP.


• Build and manage scalable data pipelines using Dagster for orchestration, dbt for transformation, and Snowflake as the primary compute and storage engine.


• Collaborate with Data Science and product stakeholders to co-develop cohort logic, derived features, and structured outputs that meet real-world scientific needs.


• Apply Generative AI techniques within transformation layers—using LLMs for named entity recognition, document summarization, classification, and schema alignment.


• Write robust, testable, and version-controlled code that adheres to CI/CD and data governance best practices.


• Implement data validation and observability frameworks to ensure quality, trust, and reproducibility of datasets.


• Document transformation logic, assumptions, and data lineage in collaboration with metadata and cataloging systems.


• Contribute to the evolution of the Data Platform by helping define standards, patterns, and best practices around GenAI and platform-scale data engineering.

About You

• You have 5+ years of experience in data engineering, ideally with at least 2 years working in healthcare or life sciences, including direct exposure to EHR datasets.


• Experience with ontologies and biomedical schemas (e.g. UMLS, LOINC, ICD9/10, MeSH, etc.)]


• Experience and understanding of modalities found within EHR datasets incl. Billing claims, lab results, visit notes, images


• Experience in biomedical feature engineering, e.g. variable transformations and derivatives


• You’re fluent in SQL and Python, and you’ve built and maintained production-grade pipelines that support analytics, science, or operational workflows.


• You have hands-on expertise with modern data infrastructure, including:


• You’re experienced in applying GenAI techniques within pipelines, including prompt engineering, LLM-based entity extraction, and classification/summarization workflows.


• You value clarity, documentation, and structured thinking—especially when working with complex data like healthcare records.


• You have a growth mindset and are excited to build bridges between isolated data environments and governed, shared models that power scientific innovation.


• Bonus: You’ve worked in regulated or privacy-sensitive data environments, and you’re familiar with governance models for PHI or sensitive data

Formation Bio is prioritizing hiring in key hubs, primarily the New York City and Boston metro areas, with additional growth in the Research Triangle (NC) and San Francisco Bay Area. Please only apply if you reside in these locations or are willing to relocate.

Compensation:

The target salary range for this role is: $230,000 - $280,000.

Salary ranges are informed by a number of factors including geographic location. The range provided includes base salary only. In addition to base salary, we offer equity, comprehensive benefits, generous perks, hybrid flexibility, and more. If this range doesn't match your expectations, please still apply because we may have something else for you.

You will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

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