Principal Product Manager, Enterprise Data Products & AI

Fanatics Commerce is the global leader in licensed sports merchandise, operating a vertically integrated platform that designs, manufactures, and delivers officially licensed apparel, jerseys, headwear, and collectibles for major leagues, teams, and events worldwide. With more than 900 e-commerce sites and a global omnichannel presence across digital, in-venue, and retail, Fanatics Commerce reaches fans in over 180 countries and powers official fan experiences for many of the world's most iconic sports properties. At Fanatics, we bring our BOLD Leadership Principles to life every day - building championship teams, obsessing over fans, acting with entrepreneurial speed, and delivering with a determined and relentless mindset. ROLE OVERVIEW Fanatics Tech is executing one of the most ambitious supply chain transformations in sports retail, rebuilding the technology backbone across product creation, merchandising, inventory, order management, sourcing, and fulfillment operations — and at the center of that transformation is data. As Principal Product Manager, you will own the vision, strategy, and roadmap for Fanatics' enterprise supply chain data products and semantic layer, creating a single source of truth for both people and AI across a rapidly expanding ecosystem of applications, agents, and decision-makers. This is a senior individual contributor role operating with a high degree of autonomy across complex, cross-functional programs in partnership with data and engineering leaders, domain PMs, and business stakeholders. The Principal Product Manager, Enterprise Data Products & AI delivers business and fan impact through BOLD leadership and execution excellence, leveraging data, automation, and AI-enabled insights. HOW WILL YOU DRIVE IMPACT Success is measured by the ability to deliver results through BOLD capabilities and measurable outcomes. Team & Leadership Impact (Build Championship Teams) Partner closely with data engineering, architecture, analytics, and domain product leaders to align enterprise data product strategy with the broader ERP and supply chain transformation, ensuring cross-functional dependencies are managed and roadmaps stay coherent as source systems evolve. Serve as the primary product voice for enterprise data products and BI across Supply Chain, influencing engineering, architecture, analytics, domain PMs, and business stakeholders without direct authority and driving consensus on shared business definitions, KPI calculations, and enterprise metrics. Act as a thought partner to engineering teams building enterprise data platforms, semantic capabilities, and AI agents — translating technical possibilities into meaningful business outcomes and representing the enterprise data product strategy during roadmap planning, program reviews, and executive discussions. Fan & Customer Impact (Obsessed with Fans) Own the vision for how Supply Chain and Operations stakeholders interact with data, evolving from static reporting toward self-service BI, conversational analytics, automated operational briefings, and AI-enabled experiences built on trusted enterprise data products. Champion BI products that go beyond dashboards — including contextual narratives, proactive insights, and AI-assisted decision support — grounded in certified enterprise data products that enable faster, higher-quality operational decisions. Partner with Product Creation, Merchandising, Inventory, Order Management, Sourcing, and Supply Chain Operations to ensure BI capabilities align with the business processes and decisions they are meant to improve, measuring success through adoption, decision quality, operational efficiency, and business impact. Ensure every enterprise data product is richly documented with business definitions, lineage, metadata, and certified quality standards that make data discoverable, trusted, and reusable across analytics, enterprise applications, and AI — not siloed within a single BI platform or team. Innovation & Problem Solving (Limitless Entrepreneurial Spirit) Define and execute the roadmap for making enterprise supply chain data AI-ready through semantic enrichment, metadata standards, contextualization, quality certification, and governance — transforming raw data from ERP, WMS, OMS, PLM, and other source systems into trusted, consumable products that reliably power AI. Partner with engineering to identify, productize, and scale AI capabilities and agentic workflows that deliver measurable business value across Supply Chain, establishing governance, validation, and feedback mechanisms that ensure AI outputs are trusted, explainable, and decision-grade. Stay current on emerging AI technologies — including LLM-powered analytics, conversational interfaces, AI agents, and prompt engineering — and translate new capabilities into practical product opportunities across the enterprise data portfolio. Drive the semantic layer for Supply Chain, ensuring enterprise metrics such as OTIF, inventory turns, cost of goods, and fill rates have consistent, authoritative business definitions and calculation methods that analytics and AI can rely on. Ownership & Execution (Determined & Relentless Mindset) Define, build, and govern a portfolio of enterprise supply chain data products — treating each data asset (e.g., Item Master, Bill of Materials, Inventory Position, Purchase Orders, Demand Signals, OTIF, Vendor Performance) as a managed product with documented consumers, SLAs, and evolution roadmaps. Own the data contract model, defining how enterprise data products are accessed, versioned, and evolved as source systems change, and partner with engineering to establish observable, measurable data pipelines with embedded quality checks, anomaly detection, and certification throughout the product lifecycle. Translate complex, ambiguous business problems into clear product requirements, epics, success metrics, and measurable outcomes; communicate