GenAI Data Engineer - Clinical Operations

Bristol-Myers Squibb; Princeton (NJ); On-site; USD 87,810 - 106,399; Full time

Job summary

Bristol Myers Squibb in Princeton, New Jersey, is seeking a Data Engineer for Clinical Operations. You will design and operate data platforms that power cross-study operations and biospecimen workflows, partnering with BI&T, trial teams, and data scientists to deliver scalable, governed data solutions.

The role emphasizes GenAI capabilities, Databricks, and cloud-based data engineering, with production-grade pipelines, data governance, and self-service analytics to accelerate research and

Qualifications

• 5+ years in Data Engineering, Analytics and AI/ML in cloud environments.
• Hands-on Databricks experience with Delta Lake, Unity Catalog, Workflows, Mosaic AI, MLflow.
• Proficient in Python, SQL and Spark (PySpark).
• Experience building production-grade data pipelines and data models for life sciences is a plus.
• Strong communication and stakeholder engagement skills.

Responsibilities

• Design, build, and maintain scalable data pipelines and platform components.
• Collaborate with BI&T, clinical operations teams, and data product owners.
• Develop data solutions to accelerate data usage across cross-study programs.
• Ensure data governance, lineage, and security using Unity Catalog and metadata tooling.
• Build GenAI-powered apps and NLP-driven data discovery features.
• Document processes and data structures; provide technical guidance.

Skills

Databricks

Delta Lake

Unity Catalog

Databricks Workflows

Mosaic AI

MLflow

Python

SQL

Spark

PySpark

GenAI

RAG

Prompt engineering

Tools

Databricks

MLflow

Unity Catalog

Job description

Bristol Myers Squibb in Princeton, New Jersey, is seeking a Data Engineer for Clinical Operations. You will design and operate data platforms that power cross-study operations and biospecimen workflows, partnering with BI&T, trial teams, and data scientists to deliver scalable, governed data solutions.

The role emphasizes GenAI capabilities, Databricks, and cloud-based data engineering, with production-grade pipelines, data governance, and self-service analytics to accelerate research and