ResponsibilitiesDesign and build data architecture that transforms raw and processed omics data into harmonized, AI-consumable layersBuild and optimize ETL/ELT pipelines that produce denormalized views, pre-computed aggregations, embedding-ready text representations, and feature stores optimized for AI consumptionImplement data quality monitoring, automated profiling, and validation checks across harmonization layersCreate versioned, reproducible data snapshots that support model training, evaluation, and audit requirements in a regulated environmentPartner with teams to extend harmonization patterns as modalities expand beyond genomics and proteomics into spatial transcriptomics, Perturb-Seq, single-cell, and digital pathologyDesign and maintain a semantic layer over multi-omics databases that enables AI systemsCreate schema documentation: table descriptions, column-level annotations, relationship mappings, business logic rules, and domain-specific constraintsDevelop gold-standard ...