• Act as a hands-on technical lead who not only defines the architecture but also codes, deploys, and maintains scalable ETL pipelines and data structures • Spearhead the technical implementation of the Translational Data Lake data ingestion, managing the ingestion of complex datasets (genomics, proteomics, imaging, lab data, etc.) into modern cloud architectures • Lead data engineering projects beyond the Data Lake, designing bespoke integration solutions for diverse scientific data sources across the Research organization • Design and script automated procedures to normalize unformatted data from external vendors (CROs) into a structured Common Data Model (CDM) • Partner with various functions in Research and IT to align infrastructure with scientific needs, ensuring solutions are robust, FAIR-compliant, and scalable • Develop and communicate the technical vision for biomarker data integration and reuse • Architect and implement scalable ETL procedures, APIs and front-end tools for data access and visualization • Engage stakeholders to gather requirements and incorporate feedback into design • Lead user acceptance testing (UAT) and ensure high-quality deliverables • Collaborate with IT and Translational leads to align infrastructure and governance processes • Champion FAIR principles and interoperability across translational and clinical programs