Senior Commercial Analytics Engineer - Business Decision Intelligence

Becton, Dickinson and Company (BD) is a global medical technology company dedicated to advancing the world of health™ through innovative products and solutions.

The Senior Analytics Analyst leads the design and delivery of governed semantic models, advanced dashboards, and scalable self‑service BI solutions for commercial stakeholders. The role is a lead technical position within the analytics team, responsible for driving semantic layer architecture decisions, establishing BI standards, and mentoring junior analysts.

• Semantic Layer Architecture & Governance
  • Design and implement governed semantic layer models aligned to enterprise business taxonomy, metric definitions, and data governance standards.
  • Define and enforce design patterns, naming conventions, and object hierarchies that enable consistent metric consumption.
  • Partner with Commercial Data Product Strategy and Analytics Engineering to ensure physical models are surfaced correctly.
  • Maintain semantic layer health, resolve conflicts, deprecate legacy objects, and manage version‑controlled releases.
• Advanced Dashboard & Interface Design
  • Design and deliver advanced, scalable BI dashboards and user interfaces that serve as authoritative commercial reporting surfaces.
  • Apply UX/UI principles to create intuitive, performant, and accessible analytics interfaces.
  • Establish and enforce dashboard design standards, template libraries, and component reuse patterns.
  • Lead evaluation and adoption of new BI platform capabilities to improve user experience and report performance.
• Self‑Service Enablement & Analytics Adoption
  • Reduce bespoke report requests by designing modular, reusable analytics assets.
  • Lead enablement workshops, training sessions, and office hours to build data literacy and BI platform proficiency.
  • Define and track self‑service adoption metrics, using insights to prioritize investments.
  • Collaborate with global and regional stakeholders to identify common analytics needs.
• Cross‑Functional Collaboration & Requirements Leadership
  • Lead requirements gathering sessions with senior commercial stakeholders.
  • Act as primary analytics liaison between commercial teams, Data Product Strategy, and Analytics Engineering.
  • Work with Decision Science & AI teams to ensure semantic layer objects support model explainability.
  • Represent the analytics team in data governance forums.
• Agentic AI Development & Training
  • Design and deliver agentic AI workflows that consume semantic layer assets for reporting, anomaly detection, and insight generation.
  • Define standards and best practices for AI‑assisted analytics development.
  • Partner with Decision Science & AI teams on training datasets and emerging tooling.
  • Mentor JG3 analysts in AI development practices and review AI workflow designs.
  • Establish governance controls and documentation standards for AI components.
• Mentorship & Team Standards
  • Mentor JG3 analytics analysts, conduct peer reviews of dashboard builds and semantic layer objects.
  • Contribute to development and documentation of team BI standards, style guides, and delivery frameworks.
  • Onboard and support new team members on tooling and analytics patterns.
  • Identify opportunities to improve team workflows and delivery cadences.

• Bachelor’s degree in Business Analytics, Information Systems, Computer Science, Data Science, or related field (advanced degree preferred).
• 4+ years of analytics, business intelligence, or data analysis experience in an enterprise environment.
• Advanced proficiency with at least one enterprise BI platform (Power BI, Tableau, Looker) and semantic or data modeling layers.
• Demonstrated experience designing governed semantic models, calculated metrics, and dimension hierarchies for multi‑team consumption.
• Strong SQL skills and familiarity with cloud data platforms such as Snowflake and Databricks.
• Proven ability to translate complex business requirements into scalable BI and reporting solutions.
• Strong understanding of commercial data domains: sales pipeline, revenue, forecasting, territory/account planning, and pricing.
• Experience driving self‑service analytics adoption and building analytics enablement programs.