Data Engineer, Clinical Operations Princeton - NJ - US R1604109 Posted

Position: Data Engineer, Clinical Operations Princeton - NJ - US R1604109 Posted a day ago
## Data Engineer, Clinical Operations Princeton - NJ - USFind out how well you match with this job
** Working with Us
** Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it.

You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible.

Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more:
*
* 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 deep 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,…