Data Engineer, Clinical Operations

Role: Data Engineer supporting Global Drug Development IT, specifically within Cross Study Operations and Specimen Management. Responsibilities include designing, building, and maintaining scalable data pipelines, supporting data ingestion, storage, processing, and governance, with a focus on clinical trial and biospecimen workflows. The role emphasizes leveraging cloud platforms, Databricks, and Generative AI to deliver innovative data solutions, optimize performance, and develop GenAI-powered applications for clinical operations. Collaborates with clinical study teams, biospecimen professionals, and data product owners to enhance data ecosystems, enforce data governance, and foster self-service discovery. Qualifications: 2+ years in Data Engineering, AI/ML, with hands-on experience in cloud-native platforms, Databricks, Python, SQL, Spark, and GenAI frameworks; Databricks certification preferred. Experience in designing ETL/ELT pipelines, semantic modeling for large complex datasets, and deploying AI/ML solutions in clinical or life sciences contexts is required. High-value specifics include clinical trial data, biospecimen workflows, GenAI/NLP applications, and cloud-based data platforms. The position is hybrid, located in Princeton, NJ, with some travel expectations. The role offers opportunities to contribute to innovative, life-changing work within a collaborative environment.