Analytics Engineer I, 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 I to help build and support the analytics layer on Databricks that connects curated data to the dashboards, self-service BI, and advanced analytics used across the business. This role is responsible for developing well-modeled datasets, metrics, and semantic assets that are easy for analysts and business users to consume.

This role operates as part of a deployed engineering team, working alongside an assigned Commercial business domain (e.g., Sales, Marketing, Market Access, or Medical Affairs) under the guidance of senior engineers to help keep the analytics layer aligned with that domain's needs.

The successful candidate will help analyze business and analytics requirements and build, test, and integrate the application components, tools, and utilities that support commercial reporting and analytics consumption, applying data modeling, SQL transformation, data quality, documentation, and governance practices under the guidance of senior engineers on the team.

This is an early-career role that offers strong exposure to Databricks-based analytics engineering, with the opportunity to build technical depth and grow into more senior data modeling and platform responsibilities over time.

Key Responsibilities

• Design, build, and support analytics-ready data products, curated datasets, and reusable transformation assets within a modern lakehouse environment to enable commercial reporting, self-service analytics, and business insights.

• Translate business and analytics requirements into clear data specifications, dimensional models, metrics definitions, and dataset readiness criteria aligned to internal modeling and delivery standards.

• Develop and maintain scalable SQL- and Python-based transformation logic that integrates structured and semi-structured pharma datasets such as claims, patient, sales, payer, HUB, and specialty pharmacy data.

• Apply internally developed accelerators, reusable code patterns, templates, and engineering guardrails to improve development speed, consistency, and maintainability across data products.

• Create analytics-friendly models, including fact and dimension tables, cross-domain joins, slowly changing dimensions, and business-rule-driven metrics that support dashboard, reporting, and advanced analytics consumption.

• Implement standardized data quality checks, reconciliation logic, validation routines, and anomaly detection controls to ensure datasets are accurate, complete, and trusted by downstream users.

• Document data products, metric definitions, lineage, assumptions, and known limitations in accordance with internal documentation and governance standards.

• Work as part of a deployed engineering team embedded alongside an assigned Commercial business domain, partnering with data engineers, analysts, BI developers, and business stakeholders to support dashboard and reporting use cases.

• Apply data governance standards, access controls, and compliant handling practices for sensitive and regulated data, including PII/PHI awareness.

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.

If this posting is missing required information required by local law or incorrect, contact BMS at TAEnablement@bms.com 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.

R1607597 : Analytics Engineer I, Commercialization