Data Engineer, Clinical Operations

Bristol Myers Squibb • Princeton, NJ

12h

About The Position

The Data Engineer will support the Data Engineering community in delivering data and analytics platforms for Bristol Myers Squibb’s Global Drug Development IT group, specifically within the Cross Study Operations and Specimen Management domain. This hands-on individual contributor role applies data engineering, cloud platform, and Generative AI expertise to create reliable, secure, user-friendly data ecosystems across the data product lifecycle, addressing clinical data challenges involving cross-study operations and biospecimen workflows.

The role collaborates with BI&T partners, business analysts, data engineers, Clinical Operations specialists, Specimen Management professionals, Cross-Study Operations leads, and other domain experts. It develops scalable data solutions and GenAI-enabled applications that support cross-study clinical R&D, specimen tracking, biobanking, data discovery, and consumption. The position also contributes technical guidance, documentation, engineering excellence, and knowledge sharing across the data engineering community.

Requirements

• 0–2 years of hands-on experience in Data Engineering, Analytics, and AI/ML, with demonstrated implementation and operation of data capabilities in a cloud environment.
• Hands-on expertise with Databricks, including Delta Lake, Unity Catalog, Databricks Workflows, Mosaic AI, and MLflow.
• Expertise in cloud-native data platforms, ETL/ELT pipeline design, data modeling, and semantic analytics for large, complex datasets, with hands-on DevOps experience.
• Strong proficiency in Python, SQL, Spark (including PySpark on Databricks), and GenAI frameworks.
• Hands-on experience with LLM architectures, RAG, prompt engineering, and agentic frameworks.
• Ability to create and maintain optimal pipeline architecture and semantic models for large, complex datasets.
• Experience delivering production-grade GenAI applications, predictive models, and self-service analytics tools for critical clinical or research business functions.
• Working knowledge of GenAI approaches including RAG, Chain-of-Thought, fine-tuning, vectorization, agentic frameworks, and prompt engineering to improve LLM response accuracy.
• Strong stakeholder engagement and communication skills, including explaining technical concepts to non-technical audiences and driving adoption across functional teams.
• Commitment to engineering excellence, documentation, and process improvement.

Nice To Haves

• Databricks certification, such as Databricks Certified Data Engineer Associate or Professional.
• Functional knowledge of Life Sciences R&D and clinical trial operations; experience with life sciences, clinical trial operations, or specimen/biobanking workflows is preferred.

Responsibilities

• Collaborate with BI&T partners, clinical study teams, cross-study operations leads, specimen management specialists, trial analysts and managers, domain experts, and cross-functional data teams to support adoption of the Data Platform.
• Design, build, and maintain production-grade data pipelines and platform components for Cross Study Operations and Specimen Management, including cross-trial aggregation, specimen tracking, and biobanking workflows.
• Develop scalable, robust, and interoperable data solutions to accelerate data use across cross-study clinical R&D programs.
• Optimize platform performance, scalability, interoperability, availability, and cost-effectiveness using approaches such as cloud-native parallel processing, Databricks Delta Lake, caching, and partitioning.
• Build ETL/ELT pipelines and data models using Databricks, Delta Lake, cloud-native tools, semantic modeling, and interoperability standards.
• Partner with business and data product owners on technical delivery, data standardization, testing, lineage, latency requirements, and access governance.
• Use Databricks Unity Catalog to manage metadata, enforce governance, and provide end-to-end data lineage.
• Contribute to self-service data discovery solutions that improve findability, accessibility, and reusability of operational and specimen data assets.
• Document processes, data structures, and technical solutions; provide clear recommendations and execute solutions across the enterprise.
• Build and deploy GenAI- and NLP-powered applications for cross-study operations and specimen management, targeting outcomes such as efficiency, traceability, insight generation, risk mitigation, and compliance automation.
• Develop and operationalize cloud-based GenAI and LLM applications using techniques such as RAG, fine-tuning, and vector embeddings.
• Use Databricks Mosaic AI and MLflow to develop, track, deploy, and manage machine learning and GenAI models.
• Stay current with GenAI, RAG, semantic search, Databricks, cloud orchestration, and containerization trends, and apply emerging best practices.
• Provide technical guidance and mentorship to junior analysts, interns, and vendor resources on Databricks, technical practices, and business alignment.
• Promote continuous learning, engineering excellence, and knowledge sharing across the data engineering community.

Benefits

• Comprehensive benefit plans, including wellbeing support, retirement and financial protection benefits, and medical, dental, vision, life, and disability insurance offerings.
• Flexible Time Off without a set accrual limit for eligible U.S.-based exempt employees, subject to manager approval.
• Paid vacation for eligible non-exempt employees, RayzeBio employees, and employees located in Puerto Rico.
• 11 paid company holidays each year; eligible non-exempt employees also receive 3 optional holidays.
• Depending on eligibility, paid sick leave, up to two paid volunteer days per year, summer hours flexibility, and leaves of absence for medical, personal, parental, caregiver, bereavement, or military needs.
• Eligible employees may receive an annual Global Shutdown between Christmas Day and New Year's Day.
• Potential eligibility for discretionary cash incentives and stock opportunities.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: No Education Listed