Opportunity Description
Responsibilities
- Design and build data architecture that transforms raw and processed omics data into harmonized, AI-consumable layers
- Build and optimize ETL/ELT pipelines that produce denormalized views, pre-computed aggregations, embedding-ready text representations, and feature stores optimized for AI consumption
- Implement data quality monitoring, automated profiling, and validation checks across harmonization layers
- Create versioned, reproducible data snapshots that support model training, evaluation, and audit requirements in a regulated environment
- Partner with teams to extend harmonization patterns as modalities expand beyond genomics and proteomics into spatial transcriptomics, Perturb-Seq, single-cell, and digital pathology
- Design and maintain a semantic layer over multi-omics databases that enables AI systems
- Create schema documentation: table descriptions, column-level annotations, relationship mappings, bu...
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