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Principal Commercial Analytics Engineer - Business Decision Intelligence

Job in Covington, Newton County, Georgia, 30014, USA
Listing for: Becton Dickinson
Full Time position
Listed on 2026-07-07
Job specializations:
  • IT/Tech
    Business Intelligence
Job Description & How to Apply Below

We Are The People Who Give Possibilities Purpose

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.

Job Description

Role Summary

The Principal Analytics Analyst is a thought leader and strategic driver for the commercial analytics semantic layer and BI user experience. This role influences the development and drives the execution of the analytics platform operating plan, establishing the enterprise-wide vision for how commercial data is modeled, governed, and consumed by business users. The Principal Analyst shapes semantic layer strategy, governs metric standards across Regions and Business Units, leads the most complex multi-stakeholder BI programs, and serves as an expert voice in cross-functional forums on data product strategy, analytics governance, and self-service enablement at scale.

Key Responsibilities

Enterprise Semantic Layer Strategy & Vision

  • Define and drive the enterprise semantic layer strategy for commercial 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 standards.
  • Lead the evaluation, selection, and adoption of semantic layer and BI platform capabilities in partnership with IT, Data Engineering, and enterprise architecture teams.
  • Serve as the authoritative voice on semantic layer design trade-offs, resolving escalated conflicts between business metric definitions and physical data model constraints.

Global Self-Service Analytics Enablement

  • Own the global self-service analytics strategy, defining the operating model, tooling standards, and enablement programs that allow commercial users across all Regions and Business Units to access governed insights independently.
  • Lead the design of modular, reusable analytics asset libraries that eliminate bespoke reporting and accelerate insight delivery across the commercial organization.
  • Define self-service maturity frameworks and adoption metrics, using data to prioritize investments and demonstrate the business value of analytics platform improvements.
  • Champion data literacy across the commercial organization through executive-level enablement programs, community of practice initiatives, and stakeholder education.

Analytics User Experience & Interface Excellence

  • Define UX/UI standards and design principles for the commercial analytics interface, ensuring that dashboards and reporting surfaces are intuitive, performant, and aligned to user needs at all levels of the organization.
  • Lead the design of the most strategically critical BI dashboards and executive reporting surfaces, in close partnership with senior commercial leaders.
  • Establish a governed component and template library for BI development across the analytics team, enabling consistent, high-quality delivery at scale.
  • Drive continuous improvement of the analytics user experience through structured feedback loops, usability research, and adoption analytics.

Metric Governance & Commercial Data Standards

  • Partner with Commercial Data Product Strategy to co-own the enterprise business glossary, metric registry, and commercial KPI framework.
  • Lead cross-functional forums to align commercial stakeholders, data engineering, and governance teams on metric definitions, calculation methodologies, and data lineage.
  • Resolve escalated metric conflicts and discrepancies across Regions, Business Units, and reporting platforms, establishing single sources of truth for key commercial KPIs.
  • Ensure all semantic layer assets meet data governance, privacy, and access control requirements in partnership with enterprise data governance teams.

Agentic AI Development & Training

  • Define and drive the enterprise strategy for agentic AI…
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