Senior Manager, Data Engineer, Clinical Operations

At Bristol Myers Squibb, our employees often ask, “Who are you working for?”—a question that fuels collaboration, accountability, and urgency in our work. Our purpose-driven culture inspires us to discover, develop, and deliver innovative medicines to prevail over serious diseases. We offer uniquely interesting and meaningful work, opportunities for growth, and a supportive environment that values inclusion, wellbeing, flexibility, and comprehensive benefits. This is work that transforms the lives of patients, and the careers of those who do it.

Position Summary:

As a Senior Manager, Data Engineer, you will play a vital role in supporting the broader Data Engineering community to deliver cutting-edge data and analytics platforms for our Global Drug Development (GDD) Patient & Site engagement and Feasibility & Forecasting domain.

We seek a candidate who excels at creating innovative, reliable, secure, and easy-to-use data ecosystems that support the full data product lifecycle — including ingesting, storing, processing, governing, and interacting with data.

You will collaborate closely with BI&T partners, business analysts, and data engineers, as well as Clinical Operations specialists, Trial Management professionals, and other domain experts to support various data-driven initiatives and enhance the overall BMS data ecosystem. Additionally, you will be expected to leverage Generative AI (GenAI), Databricks, and semantic technologies to drive innovation and efficiency within our data platforms.

Key Responsibilities:

• Support and contribute to cross-functional teams for all AI and Data initiatives across Clinical Trial Operations product lines, helping drive critical programs forward in a lean, high-impact environment.
• Develop and enhance data solutions to accelerate data usage across clinical R&D, ensuring robustness, interoperability with consumer applications, and scalability.
• Collaborate with BI&T partners, clinical study teams, Clinical trial analysts, trial managers, clinical operations leads, domain experts, and cross-functional leaders in data engineering, data product teams, and data operations to support effective adoption of our Data Platform.
• Partner with business and data product owners to deliver solutions for data product development, standardization, testing, lineage, meeting latency requirements, and ensuring access governance across clinical trial data assets.
• Optimize the data platform for performance, scalability, interoperability, availability, and cost-effectiveness using techniques such as cloud-native parallel processing, Databricks Delta Lake, caching, and partitioning.
• Utilize Databricks Unity Catalog to enforce data governance, manage metadata, and ensure end-to-end data lineage across clinical trial data products.
• Contribute to the development of self-service data discovery solutions, fostering findability, accessibility, and reusability of clinical trial operational data assets.
• Maintain documentation of processes, structures, and knowledge sharing; deliver strong technical recommendations and execute solutions effectively across the enterprise.
• Build and deploy GenAI-powered and NLP-driven applications that deliver measurable outcomes across clinical trial operations, including efficiency gains, trial timeline acceleration, risk mitigation, and compliance automation.
• Collaborate with data product owners, engineers, and data scientists to develop and operationalize cloud-based GenAI and LLM-powered applications, utilizing techniques such as RAG, fine-tuning, and vector embeddings to deliver high-quality data discovery and consumption features for clinical operations workflows.
• Stay current on technology trends in GenAI, RAG, semantic search, Databricks, cloud orchestration, and containerization; apply emerging best practices to optimize platform performance, scalability, and cost-effectiveness.
• Provide guidance and mentorship to junior analysts, interns, and vendor resources on Databricks, technical best practices, and business alignment, fostering a culture of continuous learning and improvement.

Qualifications & Experience:

• 7+ years of cross-domain experience in Data Engineering, Analytics, and AI/ML, with proven hands-on experience implementing and operating data capabilities and solutions in a cloud environment.
• Strong stakeholder engagement and communication skills; ability to influence and drive adoption of data solutions across functional teams.
• Domain knowledge across Clinical Trail Delivery, including feasibility, site selection, forecasting and trial execution is a strong plus.
• 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 in cloud-native data platforms, ETL/ELT pipeline design, data modeling, and semantic analytics for large-scale, complex datasets, with hands-on DevOps experience.

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