Sr. Data & AI Engineer, Commercialization

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. Key Responsibilities • Build, test, and integrate the application components, tools, and utilities that keep the team’s Databricks-native environment running reliably. • Own the health of the Databricks application environment day to day — jobs, workflows, notebooks, Unity Catalog — identifying and resolving issues proactively. • Design and build AI for Engineering: agents, copilots, and LLM-assisted tooling that predict and fix data quality problems and improve the team’s delivery speed. • Build the observability layer — monitoring, alerting, dashboards — that surfaces issues before they affect downstream consumers. • Build accelerators and reusable frameworks (using tools such as Claude Code and GitHub Copilot) that reduce repetitive engineering work across the team. • Develop ETL/ELT pipelines on Databricks, PySpark, SQL, and AWS (Glue, Lambda, S3, Athena) that hold up at production scale. • Lead root cause analysis on production issues, driving fixes and process changes that prevent recurrence. • Set the technical standards other engineers on the team will build to. • Partner closely with the Platform Engineering team so tooling and infrastructure integrate cleanly. • Bring CI/CD and infrastructure-as-code discipline to how the team ships. • Mentor junior engineers on observability, automation, and applied use of AI to improve engineering delivery. Skills & Competencies • Strong command of Python, PySpark, and SQL — sufficient to build automation and monitoring tooling, not just write transformation logic. • Real production experience running a Databricks environment — Delta Lake internals, Unity Catalog, Workflows. • A track record of building AI agent or LLM tooling that has measurably improved an engineering team's delivery. • A strong orientation toward observability as a default practice rather than an afterthought. • Comfort with agent frameworks (LangChain, LangGraph, CrewAI, AutoGen, or similar) and sound judgment on where they are genuinely useful. • Working depth in AWS's data services — Glue, Lambda, S3, Athena — sufficient to inform architecture decisions. • A habit of writing maintainable code, reviewing others' code constructively, and having previously set technical standards for a team. • Sound understanding of data governance, with the ability to build access controls in rather than add them after the fact. • Strong root-cause-analysis discipline and the ability to communicate technical findings clearly to both engineers and non-technical stakeholders. Qualifications & Experience • A degree in Computer Science, Engineering, Data Science, Information Systems, or a related field. • 6–8 years of experience building and owning production systems, ideally with substantial Databricks experience. • Experience building monitoring or data-quality tooling from the ground up, rather than configuring existing dashboards. • Experience building AI-for-Engineering tooling that has measurably improved a team's delivery — this is a key differentiator for this role. • A track record of mentoring engineers or setting technical direction for a team. • Preferred: experience with pharma commercial data (claims, sales, payer, patient, HUB) and the integration challenges typical of these datasets. Preferred: AWS, Databricks, or related certifications. We hire for skills and capabilities, not just credentials – if this role excites you, but doesn’t perfectly match your resume, we encourage you to apply anyway. How We Work Where you work matters – because collaboration, innovation and patient impact happen in many settings. Our roles are structured across four work models: site-essential, site-by-design, field-based and remote-by-design. The model assigned to this role is based on its core responsibilities. Learn more at https://careers.bms.com/ways-of-working. Supporting People with Disabilities BMS is dedicated to ensuring that people with disabilities can excel through a transparent recruitment process, reasonable workplace accommodations/adjustments and ongoing support in their roles. Applicants can request a reasonable workplace accommodation/adjustment prior to accepting a job offer. If you require reasonable accommodations/adjustments in completing this application, or in any part of the recruitment process, direct your inquiries to adastaffingsupport@bms.com . Visit careers.bms.com/eeo-accessibility to access our complete Equal Employment Opportunity statement. Candidate Rights BMS will consider qualified applicants with arrest and conviction records, pursuant to applicable laws in your area. For roles based in Los Angeles County only: If you live in or expect to work from Los Angeles County if hired for this position, please visit this page for important additional information: https://careers.bms.com/california-residents/ For roles based in Washington State only: If you live in or expect to work from Washington State if hired for this position, please visit this page for important information about the Washington Fair Chance Act. Data Protection We will never request payments, financial information, or social security numbers during our application or recruitment process. Learn more about protecting yourself at https://careers.bms.com/fraud-protection . Any data processed in connection with role applications will be treated in accordance with applicable data privacy policies and regulations. 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