Senior Commercial Analytics Engineer - Business Decision Intelligence

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Role Summary

The Senior Analytics Analyst leads the design and delivery of governed semantic models, advanced dashboards, and scalable self-service BI solutions for commercial stakeholders. This role takes a lead technical role within the analytics team, driving semantic layer architecture decisions, establishing BI standards, and mentoring junior analysts. The Senior Analyst brings specialized expertise in semantic modeling, user interface design for analytics, and cross-functional stakeholder engagement, ensuring that commercial data products are consumed consistently and effectively across Regions and Business Units.

Key Responsibilities

• Lead the design and implementation of governed semantic layer models aligned to enterprise business taxonomy, metric definitions, and data governance standards.
• Define and enforce semantic layer design patterns, naming conventions, and object hierarchies that enable consistent metric consumption across all BI and analytics tools.
• Partner with Commercial Data Product Strategy and Analytics Engineering teams to ensure physical data models are correctly surfaced through the semantic layer.
• Maintain semantic layer health, resolving conflicts, deprecating legacy objects, and managing version-controlled releases.

• Design and deliver advanced, scalable BI dashboards and user interfaces that serve as authoritative commercial reporting surfaces for senior business stakeholders.
• Apply UX/UI design principles to create intuitive, performant, and accessible analytics interfaces that drive self-service adoption.
• Establish and enforce dashboard design standards, template libraries, and component reuse patterns across the analytics team.
• Lead the evaluation and adoption of new BI platform capabilities that improve user experience and report performance.

• Drive the reduction of bespoke report requests by designing modular, reusable analytics assets that empower business users to self-serve.
• Lead enablement workshops, training sessions, and office hours that build data literacy and BI platform proficiency across commercial user communities.
• Define and track self-service adoption metrics, using insights to prioritize semantic layer and dashboard investments.
• Collaborate with global and regional stakeholders to identify common analytics needs that can be met through shared, governed assets.

• Lead requirements gathering sessions with senior commercial stakeholders, translating complex analytical needs into scalable BI and semantic layer solutions.
• Act as a primary analytics liaison between commercial business teams, Data Product Strategy, and Analytics Engineering to align reporting needs with data model capabilities.
• Partner with Decision Science & AI teams to ensure semantic layer objects are available and consistent for use in model explainability and output dashboards.
• Represent the analytics team in cross-functional data governance forums, contributing to metric standardization and data product prioritization.

• Lead the design and delivery of agentic AI workflows that consume semantic layer assets to automate commercial reporting, anomaly detection, and insight generation.
• Define standards and best practices for AI-assisted analytics development, including prompt engineering patterns, output validation frameworks, and human-in-the-loop review processes.
• Partner with Decision Science & AI teams to curate and maintain high-quality training datasets derived from governed BI assets and commercial data products.
• Evaluate and pilot emerging agentic AI tooling and LLM-powered analytics capabilities, recommending adoption pathways aligned to the analytics platform roadmap.
• Mentor JG3 analysts in agentic AI development practices, reviewing AI…