Analytics Engineer II, 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.

Position Summary

The Commercial Data & AI HYD team is seeking an Analytics Engineer II to build and own the analytics-layer transformations that connect curated data to the dashboards, self-service BI, and advanced analytics used across the business.

This role operates as part of a deployed engineering model, working closely with an assigned Commercial business domain (e.g., Sales, Marketing, Market Access, or Medical Affairs) to keep the analytics layer aligned with how that part of the business actually operates.

The successful candidate will analyze business requirements and build, test, and integrate the application components, tools, and utilities that support commercial reporting and analytics consumption, while owning the transformation logic, dimensional models, and metrics definitions for assigned data domains on the Databricks Lakehouse.

This role offers the opportunity to build strong technical depth in analytics engineering on Databricks, with growth potential toward more senior data modeling and solution architecture responsibilities.

Key Responsibilities

• Design, build, and own analytics-layer transformations, semantic models, and metrics for assigned data domains, turning curated data into trusted, self-serve analytics products on Databricks.
• Analyze business requirements and build, test, and integrate the application components, tools, and utilities that support commercial reporting and analytics consumption.
• Build analytics-ready data models — star/snowflake schemas, conformed dimensions, fact tables — that turn commercial business logic into consistent, reusable structures.
• Apply performance and cost-optimization practices for Databricks workloads within assigned pipelines, including cluster configuration and Delta Lake optimization (Z-ordering, partitioning, OPTIMIZE/VACUUM).
• Develop and maintain SQL- and Python-based transformation logic that integrates structured and semi-structured commercial datasets (sales, claims, patient, payer, HUB, specialty pharmacy).
• Implement data quality checks, validation routines, and reconciliation logic for assigned datasets, following established testing and documentation standards.
• Document data products, metric definitions, lineage, and known limitations in accordance with internal governance standards.
• Work as part of a deployed engineering team embedded with an assigned Commercial business domain, partnering with analysts, BI developers, and business stakeholders to support dashboard and reporting use cases.
• Apply data governance standards and access controls for sensitive and regulated data, including PII/PHI awareness.
• Provide guidance to Analytics Engineer I team members on data modeling and engineering best practices.
  
  

Skills & Competencies

• Strong proficiency in SQL and Python for analytics transformations, data modeling, and validation.
• Hands-on experience with Databricks (notebooks, jobs/workflows) and working knowledge of Delta Lake concepts (ACID tables, Z-ordering, partitioning).
• Solid experience with dimensional data modeling — star/snowflake schemas, conformed dimensions, fact tables, SCD handling.
• Familiarity with lakehouse/medallion architecture concepts (bronze/silver/gold layers).
• Working knowledge of cloud data engineering fundamentals (e.g., AWS storage, compute, and IAM concepts).
• Experience with data quality practices, including profiling, validation, and reconciliation.
• Working knowledge of software engineering practices including Git/version control, code reviews, and CI/CD.
• Familiarity with BI/visualization tools (Tableau, Power BI) and a clear sense of what makes a dataset genuinely self-service.
• Strong problem-solving and communication skills, with the ability to work independently on well-defined analytics domains.
  
  

Comfort working as part of a deployed team embedded within a business domain, adapting to domain-specific priorities.

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 [HIDDEN TEXT]. 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/

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R1607741 : Analytics Engineer II, Commercialization