Associate Director, Global Sales Analytics Engineering - Business Decision Intelligence

Associate Director, Global Sales Analytics Engineering Lead

BD is one of the largest global medical technology companies in the world. Advancing the world of health™ is our Purpose, and it's no small feat. It takes the imagination and passion of all of us—from design and engineering to the manufacturing and marketing of our billions of Med Tech products per year—to look at the impossible and find transformative solutions that turn dreams into possibilities.

The Associate Director, Global Sales Analytics Engineering Lead is the senior people leader responsible for the strategy, delivery, and continuous evolution of the commercial analytics semantic layer and business intelligence engineering function. This role owns the enterprise vision for how commercial sales data is modeled, governed, and consumed by business users globally — and builds the team, operating model, and platform capabilities required to deliver governed, scalable, and trusted analytics at scale.

A defining priority for this role is leading the transformation of the commercial analytics function from reactive, dashboard-centric reporting to a proactive, AI-ready analytics model — where governed data products, predictive signals, and intelligent alerting replace static reports as the primary vehicle for commercial insight delivery. This leader will champion the architectural and cultural shift required to move the organization from answering yesterday's questions to anticipating tomorrow's decisions.

As a member of the commercial analytics leadership team, this role partners directly with peers across Commercial Data Product Strategy, Decision Science & AI, Data Engineering, and IT to shape the enterprise data and analytics platform roadmap. The Associate Director leads a team of JG3–JG5 analysts and senior individual contributors, setting performance expectations, developing talent, and creating a culture of technical craftsmanship, stakeholder focus, and continuous improvement.

Key Responsibilities

• Lead, manage, and develop a high-performing team of Analytics Analysts (JG3–JG5) and senior individual contributors across semantic layer engineering and BI development disciplines.
• Set clear performance expectations, provide ongoing coaching and feedback, and conduct formal performance and development reviews for all direct reports.
• Own team hiring, onboarding, and workforce planning in partnership with HR and analytics leadership, ensuring the team has the skills and capacity to deliver on the roadmap.
• Build a team culture of technical excellence, accountability, stakeholder orientation, and continuous improvement.
• Represent the analytics engineering function on the commercial analytics leadership team, contributing to cross-functional strategy, prioritization, and organizational decisions.

Enterprise Semantic Layer Strategy & Governance

• Define and own the enterprise semantic layer strategy for commercial sales analytics — establishing the long-term vision for how business metrics, dimensions, and hierarchies are governed and consumed globally.
• Set the direction for semantic layer architecture across tooling platforms, ensuring scalability, consistency, and alignment to enterprise data governance and access control standards.
• Serve as the ultimate authority on semantic layer design trade-offs, resolving escalated conflicts between business metric definitions and physical data model constraints.
• Partner with Commercial Data Product Strategy to co-own the enterprise business glossary, metric registry, and commercial KPI framework.
• Lead cross-functional governance forums to align commercial stakeholders, data engineering, and enterprise architecture teams on metric definitions, calculation methodologies, and data lineage.

Global Self-Service Analytics Operating Model

• Own the global self-service analytics operating model — defining the standards, tooling, enablement programs, and governance processes that allow commercial users across all Regions and Business Units to access governed insights independently.
• Define self-service maturity frameworks, adoption KPIs, and investment priorities, using data to demonstrate business value and guide platform…