Data Engineering Manager

Role overview

Lead a data engineering team while remaining hands-on in building and operating a cloud data platform for complex healthcare information. The work spans ingestion, transformation, governance, and performance, with data products supporting analytics, machine learning, and generative AI use cases.

Responsibilities - Coach and develop the team while setting engineering practices that support collaboration and continuous improvement. - Design and evolve a cloud data platform for sources such as medical and prescription claims, EHR, CCLF, and BCDA data. - Build and operate batch, streaming, and FHIR API ingestion patterns, plus transformation and normalization pipelines. - Improve platform and pipeline performance, reliability, scalability, and cost efficiency. - Establish data governance, access controls, encryption, and documentation for architecture, lineage, metadata, and ETL/ELT processes. - Partner with data science, software, QA, product, business, and DevOps teams on trusted data assets and automated deployment.

Requirements - 8+ years in data engineering, including leadership of production cloud data platforms and development of technical talent. - Strong Python and SQL skills and experience with modern ETL/ELT frameworks. - Hands-on experience with Databricks, Snowflake, AWS, and transformation tools such as dbt or SQLMesh. - Ability to design modular, maintainable codebases that support reuse, testing, and collaboration. - Experience with healthcare data management and the governance and controls needed for HIPAA and SOC 2 compliance.

Benefits and work setup - Remote role open to U.S. candidates, with preference for people near Atlanta or Philadelphia. - Benefits listed include health, dental, and vision coverage, retirement savings, equity and incentive compensation, flexible PTO, paid holidays, flexible hours, and paid leave.