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Senior, highly specialized clinical data role at a Tier‑1 biotech yields medium competition.
Requires clinical/biomarker domain experience and CDISC knowledge, limiting cross-industry transferability.
Explicit 8+ years and specific clinical data, Databricks, and regulatory requirements make shortlisting highly strict.
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Design, build, and operate end-to-end data ingestion pipelines for biomarker and clinical data supporting clinical trials.
Implement automated data validation, error handling, and remediation workflows to ensure data quality and traceability.
Collaborate with internal biomarker labs and external CROs/vendors to onboard new assays and maintain data transfer specifications and mapping logic.
8+ years experience with a Bachelor's in Computational Biology, Bioinformatics, AI, Computer Science, Data Engineering, or related field; PhD is a plus.
3+ years experience in data engineering or platform engineering roles; experience with biomarker/clinical data or clinical research environment highly desirable.
Strong Python programming skills, database design expertise, and experience with Databricks.
Experience with workflow/orchestration tools (Airflow, Nextflow, snakemake), agentic automation, Codex workflows, HPC/cloud platforms (e.g., AWS), version control (Git), CI/CD, containerization (Docker), and familiarity with clinical data standards (CDISC/SDTM/ADaM).
Technically hands-on with strong programming and data engineering background focused on clinical and biomarker data pipelines.
Experienced in integrating AI-driven automation and workflow orchestration specifically for translational and clinical research data.
Capable of collaborating cross-functionally with computational biologists, translational scientists, labs, and external vendors to ensure standardized, high-quality data ingestion.