GenAI-Powered Data Engineer - Clinical Operations

Bristol-Myers Squibb Co; Princeton (NJ); On-site; USD 66,000 - 79,000; Full time

Benefits offered by this job

Wellbeing support

Retirement plan

Insurance package

Flexible time off

Job summary

Bristol Myers Squibb is seeking a Data Engineer in Princeton, NJ to support the Cross Study Operations and Specimen Management data platforms. You will design scalable data pipelines, implement Delta Lake-based data models, and apply GenAI techniques to deliver robust data solutions for complex clinical datasets.

You will collaborate with BI&T, clinical teams, and data engineers to ensure data quality, governance, and cost-efficient operations while advancing GenAI-powered capabilities

Qualifications

• 0-2 years of hands-on data engineering, analytics, and AI/ML in a cloud environment.
• Hands-on Databricks experience with Delta Lake and Unity Catalog.
• Strong Python, SQL, Spark and GenAI knowledge.
• Excellent collaboration and communication with cross-functional teams.

Responsibilities

• Design and maintain scalable data pipelines for Cross Study Operations and Specimen Management.
• Build data models and ETL/ELT processes using Databricks and Delta Lake.
• Ensure data governance, lineage, and access controls across data products.
• Collaborate with BI&T partners and clinical teams to drive adoption of data solutions.
• Develop GenAI-powered data discovery and NLP applications for life sciences workflows.

Skills

Python

SQL

Spark / PySpark

GenAI & NLP

Data pipeline design

Cloud platforms

Tools

Databricks

Delta Lake

Unity Catalog

Databricks Workflows

Mosaic AI

MLflow

Job description

Bristol Myers Squibb is seeking a Data Engineer in Princeton, NJ to support the Cross Study Operations and Specimen Management data platforms. You will design scalable data pipelines, implement Delta Lake-based data models, and apply GenAI techniques to deliver robust data solutions for complex clinical datasets.

You will collaborate with BI&T, clinical teams, and data engineers to ensure data quality, governance, and cost-efficient operations while advancing GenAI-powered capabilities