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Senior role at a Tier-1 employer in a metro, but specialized biomarker skills limit candidate density.
Strong clinical biomarker and CDISC/clinical-data focus reduces cross-industry transferability of experience.
Explicit 8+ years requirement plus mandatory clinical data and technical skills makes screening strict.
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Design, build, and maintain end-to-end data ingestion pipelines for biomarker and clinical data supporting clinical trials.
Implement automated validation, quality control, error handling and remediation workflows to ensure data quality and traceability.
Integrate automation and AI workflows, collaborate with labs and vendors to onboard assays, and produce study-specific analysis bundles within defined timelines.
8+ years work experience with at least 3 years in data or platform engineering roles.
Bachelor’s degree in Computational Biology, Bioinformatics, AI, Computer Science, Data Engineering, or related field; PhD is a plus.
Strong Python programming and database design skills; experience with Databricks.
Experience with clinical data formats/standards (CDISC/SDTM/ADaM), workflow orchestration tools, agentic automation, AI workflow development, and knowledge of clinical biomarker assays.
Experienced in managing complex clinical and biomarker data in regulated or research environments.
Proficient in designing scalable, automated data pipelines and standardization frameworks involving multiple stakeholders including CROs and labs.
Comfortable working with AI/automation tools in data engineering, with strong collaborative skills to interface with cross-functional teams and external vendors.