Principal Commercial Analytics Engineer - Business Decision Intelligence

Becton Dickinson Medical Devices•Vernon Hills, IL

1d•Onsite

About The Position

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 MedTech products per year—to look at the impossible and find transformative solutions that turn dreams into possibilities. 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.

Requirements

Bachelor's degree in Business Analytics, Information Systems, Computer Science, Data Science, or a related field required.
Advanced degree strongly preferred.
6+ years of progressive experience in analytics, business intelligence, or data analysis, with increasing scope and seniority.
Deep expertise in enterprise semantic layer design and governance across one or more platforms (e.g., LookML/Looker, AtScale, dbt Metrics, Power BI Semantic Models, Microsoft Fabric).
Proven track record driving enterprise-scale self-service analytics programs across multiple Business Units or Regions.
Advanced SQL skills and strong working knowledge of cloud data platforms (e.g., Snowflake, BigQuery, Databricks).
Demonstrated experience as a thought leader in analytics — shaping platform strategy, metric standards, or BI architecture direction.
Deep understanding of commercial data domains: revenue, pipeline/opportunity, forecasting, pricing/CPQ, territory/account planning, and commercial KPIs.
Strong executive communication and stakeholder influence skills, with experience presenting to and advising senior business leaders.
Experience partnering with data governance, data engineering, and decision science functions in a matrixed, global organization.

Nice To Haves

Experience defining and implementing enterprise metric frameworks, KPI registries, or commercial data glossaries.
Hands-on experience with multiple semantic layer platforms and the ability to advise on tool selection and migration.
Familiarity with AI/ML output visualization, model explainability dashboards, and decision intelligence use cases.
Experience in MedTech, Life Sciences, or similarly regulated and complex commercial environments.
Global experience leading analytics programs that serve multiple Regions and Business Units with shared assets.
Prior experience in a principal, staff, or lead analyst role with informal or formal people leadership responsibilities.

Responsibilities

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.
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.
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.
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.
Define and drive the enterprise strategy for agentic AI integration within the commercial analytics platform, establishing the vision for how AI agents consume, generate, and augment governed semantic layer assets.
Lead the architecture and governance of AI training data programs, ensuring commercial analytics outputs used for model development meet quality, lineage, and compliance standards.
Partner with Decision Science & AI and enterprise architecture teams to define reference architectures for agentic AI workflows embedded in commercial reporting, forecasting, and decision intelligence use cases.
Establish enterprise-wide standards for prompt engineering, AI output validation, and human-in-the-loop governance across commercial analytics agentic workflows.
Represent the analytics function in senior cross-functional forums on AI platform strategy, contributing to investment decisions, risk governance, and responsible AI frameworks.
Mentor JG3 and JG4 analysts in agentic AI development and training practices, fostering a culture of responsible, governed AI adoption within the commercial analytics team.
Track and assess the maturity of agentic AI capabilities across the commercial analytics ecosystem, defining roadmap priorities and success metrics that align to enterprise AI strategy.
Provide strategic technical leadership across the analytics team, influencing the roadmap, tooling decisions, and delivery model for semantic layer and BI functions.
Mentor and develop JG3 and JG4 analysts, establishing a culture of craftsmanship, continuous improvement, and stakeholder focus.
Represent the analytics function in senior cross-functional forums, contributing to enterprise data strategy, platform investment decisions, and analytics governance.
Partner with Commercial Decision Science & AI teams to ensure semantic layer assets support AI model explainability, output visualization, and executive decision dashboards.
Contribute to the hiring, onboarding, and capability development of the broader analytics team in partnership with the analytics engineering lead.