At Bristol Myers Squibb, our employees often ask, “Who are you working for?”—a question that fuels collaboration, accountability, and urgency in our work. Our purpose-driven culture inspires us to discover, develop, and deliver innovative medicines to prevail over serious diseases. We offer uniquely interesting and meaningful work, opportunities for growth, and a supportive environment that values inclusion, wellbeing, flexibility, and comprehensive benefits. This is work that transforms the lives of patients, and the careers of those who do it.
Position Summary:
As a Data Engineer , you will play a vital role in supporting the broader Data Engineering community to deliver cutting-edge data and analytics platforms for our Global Drug Development (GDD) IT group — specifically within the Cross Study Operations and Specimen Management domain.
We seek a candidate who excels at creating innovative, reliable, secure, and easy-to-use data ecosystems that support the full data product lifecycle — including ingesting, storing, processing, governing, and interacting with data. You will be a hands-on technical expert and individual contributor , applying expertise in data engineering, cloud platforms, and Generative AI to solve complex clinical data challenges across cross-study operations and biospecimen workflows, delivering high-quality, scalable data solutions.
You will collaborate closely with BI&T partners, business analysts, and data engineers, as well as Clinical Operations specialists, Specimen Management professionals, Cross-Study Operations leads , and other domain experts to support various data-driven initiatives and enhance the overall BMS data ecosystem. You will be expected to leverage Generative AI (GenAI), Databricks , and semantic technologies to drive innovation and efficiency within our data platforms.
Key Responsibilities:
Collaborate with BI&T partners, cross-study operations leads, specimen management specialists, clinical study teams, clinical trial analysts, trial managers, domain experts , and cross-functional leaders in data engineering, data product teams, and data operations to support effective adoption of our Data Platform.
Design, build, and maintain scalable, production-grade data pipelines and platform components supporting Cross Study Operations and Specimen Management product lines, including cross-trial data aggregation, specimen tracking, and biobanking workflows.
Develop and enhance data solutions to accelerate data usage across cross-study clinical R&D programs , ensuring robustness, interoperability with consumer applications, and scalability.
Optimize data platform components for performance, scalability, interoperability, availability, and cost-effectiveness using techniques such as cloud-native parallel processing, Databricks Delta Lake , caching, and partitioning.
Help design and build scalable ETL/ELT pipelines and data models using Databricks , Delta Lake, cloud-native tools, semantic modeling, and interoperability standards for large, complex cross-study and specimen datasets in life sciences.
Partner with business and data product owners to deliver hands-on technical solutions for data product development, standardization, testing, lineage , meeting latency requirements, and ensuring access governance across cross-study and specimen management data assets.
Utilize Databricks Unity Catalog to enforce data governance, manage metadata, and ensure end-to-end data lineage across cross-study and specimen management data products.
Contribute to the development of self-service data discovery solutions , fostering findability, accessibility, and reusability of cross-study operational and specimen data assets.
Maintain thorough documentation of processes, data structures, and technical solutions ; deliver clear technical recommendations and execute solutions effectively across the enterprise.
Help build and deploy GenAI-powered and NLP-driven applications that deliver…