Sr. Data & AI Engineer, Commercialization

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

• 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.

• 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

• Any data processed in connection with role applications will be treated in accordance with applicable data privacy policies and regulations.

• If this posting is missing required information required by local law or incorrect, contact BMS with the Job Title and Requisition number. Do not send application-related inquiries to this email. To check your application status, please login to your Candidate Home Account.

• R1607806 : Sr. Data & AI Engineer, Commercialization