AI Data Engineer - Hybrid Role at HHMI
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Summary
Hybrid AI Data Engineer at HHMI in Chevy Chase, MD builds AI-ready data pipelines from ingestion to content serving using Databricks, Spark, Python, and SQL — implementing medallion architecture, workflow orchestration, governance, and data quality to power AI functionality for scientific research.
Support AI initiatives at HHMI as an AI Data Engineer in Chevy Chase, MD. This hybrid position requires hands-on data engineering experience to build robust, AI-driven data pipelines.
As an integral member of HHMI, you will implement essential data pipelines to prepare institutional content for AI applications. This role demands collaboration with the Principal Knowledge & Data Architect and AI Developers to ensure quality and governance in the data flows that power AI functionalities. Contribute to HHMI's mission while directly impacting scientific advancements.
Key Responsibilities: • Build AI data pipelines from ingestion to serving content • Implement medallion architecture for data management • Own workflow orchestration with Databricks Workflows • Enforce governance patterns on data assets • Design and operate data quality mechanisms
Requirements: • 4+ years in production data engineering • Proficiency in Databricks and Spark technologies • Strong knowledge of Python and SQL • Experience with AI data engineering fundamentals • Understanding of data governance frameworks
Make a tangible difference in AI-driven science at HHMI, enhancing operational efficiencies.
As an integral member of HHMI, you will implement essential data pipelines to prepare institutional content for AI applications. This role demands collaboration with the Principal Knowledge & Data Architect and AI Developers to ensure quality and governance in the data flows that power AI functionalities. Contribute to HHMI's mission while directly impacting scientific advancements.
Key Responsibilities: • Build AI data pipelines from ingestion to serving content • Implement medallion architecture for data management • Own workflow orchestration with Databricks Workflows • Enforce governance patterns on data assets • Design and operate data quality mechanisms
Requirements: • 4+ years in production data engineering • Proficiency in Databricks and Spark technologies • Strong knowledge of Python and SQL • Experience with AI data engineering fundamentals • Understanding of data governance frameworks
Make a tangible difference in AI-driven science at HHMI, enhancing operational efficiencies.