Position Summary:

As aData Engineer, you will play a vital role in supporting the broader Data Engineering community to deliver cutting-edge data and analytics platforms for ourGlobal Drug Development (GDD) ITgroup specifically within theCross Study Operations and Specimen Managementdomain.

We seek a candidate who excels at creating innovative, reliable, secure, and easy-to-use data ecosystems that support the fulldata product lifecycleincluding ingesting, storing, processing, governing, and interacting with data. You will be ahands-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 BI26T partners, business analysts, and data engineers, as well asClinical 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 leverageGenerative AI (GenAI), Databricks, andsemantic technologiesto drive innovation and efficiency within our data platforms.

Key Responsibilities:

• Collaborate withBI26T 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 maintainscalable, production-grade data pipelines and platform componentssupporting Cross Study Operations and Specimen Management product lines, including cross-trial data aggregation, specimen tracking, and biobanking workflows.

• Develop and enhance data solutions toaccelerate data usage across cross-study clinical R26D programs, ensuring robustness, interoperability with consumer applications, and scalability.

• Optimize data platform components forperformance, scalability, interoperability, availability, and cost-effectivenessusing techniques such as cloud-native parallel processing,Databricks Delta Lake, caching, and partitioning.

• Help design and buildscalable ETL/ELT pipelines and data modelsusingDatabricks, 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 fordata product development, standardization, testing, lineage, meeting latency requirements, and ensuring access governance across cross-study and specimen management data assets.

• UtilizeDatabricks Unity Catalogto enforce data governance, manage metadata, and ensure end-to-end data lineage across cross-study and specimen management data products.

• Contribute to the development ofself-service data discovery solutions, fostering findability, accessibility, and reusability of cross-study operational and specimen data assets.

• Maintain thoroughdocumentation of processes, data structures, and technical solutions; deliver clear technical recommendations and execute solutions effectively across the enterprise.

• Help build and deployGenAI-powered and NLP-driven applicationsthat deliver measurable outcomes across cross-study operations and specimen management, including efficiency gains, specimen traceability improvements, cross-study insight generation, risk mitigation, and compliance automation

• Develop and operationalizecloud-based GenAI and LLM-powered applicationsin collaboration with data product owners, engineers, and data scientists, utilizing techniques such asRAG, fine-tuning, and vector embeddingsto deliver high-quality data discovery and consumption features for cross-study and specimen management workflows.

• LeverageDatabricks Mosaic AIandMLflowto develop, track, deploy, and manage machine learning and GenAI models at scale within cross-study and specimen management contexts.

• Stay current on technology trends inGenAI, RAG, semantic search, Databricks, cloud orchestration, and containerization; apply emerging best practices to optimize platform performance, scalability, and cost-effectiveness.

• Serve as ago-to technical expertwithin the Cross Study Operations and Specimen Management domain, providing guidance and mentorship to junior analysts, interns, and vendor resources on Databricks, technical best practices, and business alignment.

• Foster a culture ofcontinuous learning, engineering excellence, and knowledge sharingacross the data engineering community.

Qualifications 26 Experience:

• 5+ yearsof hands-on experience inData Engineering, Analytics, and AI/ML, with demonstrated expertise implementing and operating data capabilities and solutions in a cloud environment.

• Hands-on expertise with Databricks, including Delta Lake, Unity Catalog, Databricks Workflows, Mosaic AI, and MLflow;Databricks certification(e.g., Databricks Certified Data Engineer Associate/Professional) is a strong plus.

• Demonstrated expertise incloud-native data platforms, ETL/ELT pipeline design, data modeling, and semantic analyticsfor large-scale, complex datasets, with hands-on DevOps experience.

• Strong proficiency inPython, SQL, Spark (including PySpark on Databricks), and GenAI frameworks; hands-on experience withLLM architectures, RAG, prompt engineering, and agentic frameworks.

• Proficiency in creating and maintaining optimaldata pipeline architecturefor large, complex datasets, including semantic modeling within a domain preferably life sciences, clinical trial operations, or specimen/biobanking workflows.

• Demonstrated experience deliveringproduction-grade GenAI applications, predictive models, and self-service analytics tools supporting critical clinical or research business functions.

• Working knowledge ofLLM and GenAI-driven approaches, including RAG, Chain-of-Thought, fine-tuning, vectorization, agentic frameworks, and prompt engineering techniques for improving the accuracy of LLM-based responses.

• Strongstakeholder engagement and communication skills;ability to clearly articulate technical concepts to non-technical audiences and drive adoption of data solutions across functional teams.

• Commitment toengineering excellence, documentation, and process improvement;functional knowledge of Life Sciences R26D and clinical trial operations is highly preferred.

If you come across a role that intrigues you but doesn27t perfectly line up with your resume, we encourage you to apply anyway. You could be one step away from work that will transform your life and career.

The starting compensation range(s) for this role are listed above for a full-time employee (FTE) basis. Additional incentive cash and stock opportunities (based on eligibility) may be available. The starting pay rate takes into account characteristics of the job, such as required skills, where the job is performed, the employee27s work schedule, job-related knowledge, and experience. Final, individual compensation will be decided based on demonstrated experience.

Eligibility for specific benefits listed on our careers site may vary based on the job and location. For more on benefits, please visit

Benefit offerings are subject to the terms and conditions of the applicable plans in effect at the time and may require enrollment. Our benefits include:

• Health Coverage: Medical, pharmacy, dental, and vision care.

• Wellbeing Support: Programs such as BMS Well-Being Account, BMS Living Life Better, and Employee Assistance Programs (EAP).

• Financial Well-being and Protection: 401(k) plan, short- and long-term disability, life insurance, accident insurance, supplemental health insurance, business travel protection, personal liability protection, identity theft benefit, legal support, and survivor support.

0Work-life benefits include:

Paid Time Off

• US Exempt Employees: flexible time off (unlimited, with manager approval, 11 paid national holidays (not applicable to employees in Phoenix, AZ, Puerto Rico or Rayzebio employees)

• Phoenix, AZ, Puerto Rico and Rayzebio Exempt, Non-Exempt, Hourly Employees: 160 hours annual paid vacation for new hires with manager approval, 11 national holidays, and 3 optional holidays

Based on eligibility*, additional time off for employees may include unlimited paid sick time, up to 2 paid volunteer days per year, summer hours flexibility, leaves of absence for medical, personal, parental, caregiver, bereavement, and military needs and an annual Global Shutdown between Christmas and New Years Day.

All global employees full and part-time who are actively employed at and paid directly by BMS at the end of the calendar year are eligible to take advantage of the Global Shutdown.

*Eligibility Disclosure: The summer hours program is for United States (U.S.) office-based employees due to the unique nature of their work. Summer hours are generally not available for field sales and manufacturing operations and may also be limited for the capability centers. Employees in remote-by-design or lab-based roles may be eligible for summer hours, depending on the nature of their work, and should discuss eligibility with their manager. Employees covered under a collective bargaining agreement should consult that document to determine if they are eligible. Contractors, leased workers and other service providers are not eligible to participate in the program.