Senior Manager, Data Engineer, Clinical Operations
Bristol Myers Squibb
August 13, 2026
Remote friendly (Princeton, NJ)
United States
IT
Position Summary
As a Senior Manager, Data Engineer, you will support the Data Engineering community to deliver data and analytics platforms for Global Drug Development (GDD) — Patient & Site engagement and Feasibility & Forecasting.
Key Responsibilities
- Support cross-functional AI and Data initiatives for Clinical Trial Operations product lines.
- Develop and enhance data solutions to accelerate clinical R&D data usage (robustness, interoperability, scalability).
- Collaborate with BI&T, business/data analysts, data engineers, and domain experts to drive adoption of the Data Platform.
- Deliver solutions for data product development: standardization, testing, lineage, latency requirements, and access governance.
- Optimize platform performance, scalability, interoperability, availability, and cost using cloud-native parallel processing, Databricks Delta Lake, caching, and partitioning.
- Use Databricks Unity Catalog for governance, metadata management, and end-to-end lineage.
- Build self-service data discovery (findability, accessibility, reusability).
- Maintain documentation; provide technical recommendations.
- Build/deploy GenAI and NLP applications to improve efficiency, accelerate timelines, mitigate risk, and automate compliance.
- Operationalize cloud-based GenAI/LLM applications using RAG, fine-tuning, and vector embeddings.
- Stay current on GenAI/RAG/semantic search/Databricks/cloud orchestration/containerization.
- Mentor junior analysts/interns/vendor resources.
Qualifications & Experience
- 7+ years in Data Engineering/Analytics/AI-ML with hands-on cloud data capabilities.
- Strong communication and stakeholder management; ability to influence adoption.
- Databricks expertise (Delta Lake, Unity Catalog, Workflows, Mosaic AI, MLflow) and certification strong plus.
- Cloud-native data platforms; ETL/ELT, data modeling, semantic analytics; DevOps experience.
- Python, SQL, Spark (PySpark on Databricks), GenAI frameworks; LLM architectures, RAG, prompt engineering, agentic frameworks.
- Production-grade GenAI apps, predictive models, self-service analytics.
- Working knowledge of LLM/GenAI approaches (RAG, fine-tuning, vectorization, agentic frameworks, prompt engineering).
- Life sciences/clinical trial operations knowledge strongly preferred; familiarity with Veeva Vault, Medidata Rave, IRT preferred.
Benefits (as stated)
- Health Coverage; Wellbeing support; Financial wellbeing/protection (401(k), disability, life insurance, etc.).
Compensation Overview (as stated)
- Princeton, NJ: $153,770–$186,327 (full-time). Additional incentives may apply based on eligibility.
As a Senior Manager, Data Engineer, you will support the Data Engineering community to deliver data and analytics platforms for Global Drug Development (GDD) — Patient & Site engagement and Feasibility & Forecasting.
Key Responsibilities
- Support cross-functional AI and Data initiatives for Clinical Trial Operations product lines.
- Develop and enhance data solutions to accelerate clinical R&D data usage (robustness, interoperability, scalability).
- Collaborate with BI&T, business/data analysts, data engineers, and domain experts to drive adoption of the Data Platform.
- Deliver solutions for data product development: standardization, testing, lineage, latency requirements, and access governance.
- Optimize platform performance, scalability, interoperability, availability, and cost using cloud-native parallel processing, Databricks Delta Lake, caching, and partitioning.
- Use Databricks Unity Catalog for governance, metadata management, and end-to-end lineage.
- Build self-service data discovery (findability, accessibility, reusability).
- Maintain documentation; provide technical recommendations.
- Build/deploy GenAI and NLP applications to improve efficiency, accelerate timelines, mitigate risk, and automate compliance.
- Operationalize cloud-based GenAI/LLM applications using RAG, fine-tuning, and vector embeddings.
- Stay current on GenAI/RAG/semantic search/Databricks/cloud orchestration/containerization.
- Mentor junior analysts/interns/vendor resources.
Qualifications & Experience
- 7+ years in Data Engineering/Analytics/AI-ML with hands-on cloud data capabilities.
- Strong communication and stakeholder management; ability to influence adoption.
- Databricks expertise (Delta Lake, Unity Catalog, Workflows, Mosaic AI, MLflow) and certification strong plus.
- Cloud-native data platforms; ETL/ELT, data modeling, semantic analytics; DevOps experience.
- Python, SQL, Spark (PySpark on Databricks), GenAI frameworks; LLM architectures, RAG, prompt engineering, agentic frameworks.
- Production-grade GenAI apps, predictive models, self-service analytics.
- Working knowledge of LLM/GenAI approaches (RAG, fine-tuning, vectorization, agentic frameworks, prompt engineering).
- Life sciences/clinical trial operations knowledge strongly preferred; familiarity with Veeva Vault, Medidata Rave, IRT preferred.
Benefits (as stated)
- Health Coverage; Wellbeing support; Financial wellbeing/protection (401(k), disability, life insurance, etc.).
Compensation Overview (as stated)
- Princeton, NJ: $153,770–$186,327 (full-time). Additional incentives may apply based on eligibility.