Principal Product Manager - Business Intelligence & Data Products at Fanatics

Atlanta, Georgia, United States -

Full Time

Start Date

Immediate

Expiry Date

14 Aug, 26

Salary

250000.0

Posted On

16 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Product Management, Business Intelligence, Data Product Ownership, AI Strategy, Supply Chain Management, Data Governance, SQL, Semantic Layer Design, Stakeholder Management, Roadmap Planning, Data Modeling, Agile/Scrum

Industry

Manufacturing

Description

About This Role 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. At the center of that transformation is data: the need to make it trustworthy, AI-ready, and consumable across a rapidly expanding ecosystem of applications, agents, and decision-makers. As Principal Product Manager, Business Intelligence & Data Products, you will own the product vision and execution for treating enterprise data as a first-class, managed asset across Fanatics' Supply Chain Technology domains, including Inventory & Order Management, Sourcing, and Supply Chain Operations with close adjacency to Product Creation and Merch & Planning. This is not a traditional BI reporting role. You will define, govern, and continuously evolve a shared data product layer, richly documented, semantically consistent, and purpose-built to power both human analytics and AI-driven workloads. This is a senior individual contributor role. You will operate with a high degree of autonomy across complex, cross-functional programs, partnering closely with engineering leads, domain PMs, and business stakeholders to ensure the data assets underpinning Fanatics' supply chain are decision-grade, AI-ready, and built to last. How You Will Make an Impact Data Asset & Data Product Ownership This is the heart of the role. Fanatics' supply chain data spans product creation, line planning, inventory, orders, sourcing, and operations — and it must be ready not just for analysts, but for AI agents, ML models, and agentic applications. * Define, build, and govern a portfolio of 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. * Ensure every data asset is richly described: business definitions agreed by consensus, lineage documented, quality dimensions certified, and metadata thorough enough for an AI system to interpret it correctly without human intervention. * Own the data contract model — establishing formal agreements with consuming teams and applications that govern how data assets are accessed, versioned, and evolved as source systems change. * Build and maintain a discoverable, plug-and-play knowledge layer that can be connected to any application, agent, or analytics tool across the back-end technology estate — not siloed to a single BI tool or team. * Partner with engineering to establish observable, measurable data pipelines — ensuring quality checks, anomaly detection, and certification workflows are embedded in the data product lifecycle, not bolted on after. * Drive the semantic and ontology layer for supply chain: ensure enterprise metrics (e.g., OTIF, inventory turn, cost of goods, fill rates) have consistent, authoritative definitions and calculation methods that AI tools can rely on to produce decision-grade outputs. AI Readiness & Agentic Data Strategy Getting the data AI-ready is the strategic objective that sits atop everything else in this role. Raw data from source systems — WMS, ERP, OMS, PLM — is not AI-ready out of the gate. This role exists to close that gap. * Define and execute the roadmap for making supply chain data AI-consumable: denormalization, cleansing, annotation, contextual enrichment, and metadata standards applied systematically across the data product portfolio. * Govern the agent ecosystem — ensuring AI agents built on supply chain data are formalized, discoverable, documented, and operating within sanctioned boundaries. Define who can access them, in what contexts, and how they are maintained as data evolves. * Partner with engineering to accelerate the path from AI prototype to production-grade data product — identifying when citizen-built solutions are ready to be governed, productized, and scaled, and driving that transition with rigor. * Establish quality standards that make AI outputs decision-grade — not just plausible. Design and implement the human-in-the-loop checkpoints, validation layers, and feedback loops needed to keep AI-generated insights trustworthy. * Stay current on the evolving AI tooling landscape and bring emerging capability back to the team — translating it into practical roadmap opportunity within the supply chain data context. BI Experience & Analytics Delivery * Own the vision for how supply chain and operations stakeholders interact with data — driving a deliberate evolution from static reporting toward dynamic, AI-enriched analytics experiences built on trusted data foundations. * Champion BI assets that go beyond dashboards: contextual narratives, automated operational briefings, and conversational analytics grounded in certified, governed data products. * Partner with domain PMs across Inventory, Order Management, Sourcing, and Supply Chain Operations — and in close adjacency with Product Creation and Merch & Planning — to ensure BI capabilities are tightly aligned to the business processes and decisions they are meant to improve. * Ensure BI products are measured against outcomes — adoption, decision quality, and operational efficiency improvements — not just delivery. Domain Coverage This role sits primarily within Supply Chain Technology, with adjacency to Product Creation and Merch & Planning. Deep familiarity with at least two Supply Chain domains is expected; a working understanding across all is required to be effective. * Product Creation & PLM - Item, product, line plans, bill of materials, licensing, digital assets. * Merch & Planning - Assortment planning, demand signals, inventory allocation, merch performance. * Inventory & Order Management - Inventory position, order lifecycle, fulfillment events, OTIF. * Sourcing & Vendor Management - Purchase orders, vendor performance, compliance data, costing. * Supply Chain Operations - Warehouse events, production/shopfloor, logistics, distribution performance. Roadmap & Portfolio Management * Own and maintain the BI and data product roadmap across supply chain domains — balancing short-term delivery needs against long-term platform evolution and AI readiness investments. * Translate complex, ambiguous business problems into clear product requirements, epics, and success metrics — working closely with engineering leads who are currently carrying PM responsibilities in this space. * Manage cross-domain dependencies and ensure the data product roadmap stays synchronized with the broader ERP/SCM transformation as source systems evolve. * Communicate roadmap status, risks, and trade-offs clearly to senior stakeholders — escalating with a recommendation, not just a problem. Data Governance & Quality * Champion data governance practices across the supply chain data estate — ensuring standards, quality expectations, access policies, and certification workflows are consistently applied and measurable. * Drive consensus on business definitions and calculation methods for enterprise metrics — particularly in areas where multiple systems or teams currently produce conflicting numbers. * Partner with data engineering to monitor data reliability, drive continuous improvement, and ensure the long-term health of the data ecosystem as source systems are replaced or upgraded. Cross-Functional Partnership & Stakeholder Management * Operate as the primary product voice for BI and data products across supply chain — building strong relationships with domain PMs, engineering leads, and business stakeholders without direct authority over any of them. * Partner with supply chain domain PMs (ERP/SCM, Inventory, Order Management, Sourcing) — and in adjacency with Product Creation and Merch & Planning PMs — to ensure the data product roadmap reflects both near-term business needs and the long-term analytical and AI ambition of each domain. * Serve as a thought partner to engineering leads building AI agents and data infrastructure — bridging the gap between what is technically possible and what creates real business value. * Actively participate in program reviews and strategic planning cycles, ensuring the data product perspective is represented in every major supply chain technology decision. What You Bring Experience & Education * 6–10 years of product management experience, with significant depth in data products, business intelligence, or analytics platform ownership in a supply chain, eCommerce, or operations technology environment. * Demonstrated track record as a senior individual contributor — driving complex, cross-functional programs from ambiguity to production without requiring a team of direct reports to do it. * Bachelor's degree in Computer Science, Information Systems, Business, or related field; advanced degree a plus but not required. AI Fluency & Data Product Mindset * Operates at the AI-Integrator to AI-Strategist level: embeds AI into product strategy, owns domain-level AI roadmap decisions, and drives informed build/buy/integrate choices. * Hands-on familiarity with modern AI tooling — including prompt engineering, LLM-powered analytics, and agentic frameworks — with the ability to evaluate, configure, and iterate on these tools in an enterprise data context. * Understands what it takes to make data AI-ready: denormalization, annotation, semantic enrichment, metadata standards, quality certification. Has done it, not just read about it. * Experience governing AI agents built on enterprise data — defining access models, documentation standards, versioning, and quality guardrails. * Experience recognizing when a citizen-developed solution is worth productizing and governing — and knowing how to lead that transition responsibly. Domain Expertise, Data Products & BI * Proven experience treating data as a product: defining data assets with consumers, SLAs, contracts, quality dimensions, and evolution roadmaps. * Deep familiarity with what makes a data asset discoverable, trustworthy, and reusable across multiple consuming teams and applications — not just within a single BI tool. * Strong understanding of BI platforms (e.g., MicroStrategy, Snowflake, Tableau, Power BI) and a track record of partnering with data engineering teams to deliver trusted, certified data sources. * Experience defining and enforcing semantic layers, business glossaries, and ontology standards — with a strong point of view on the difference between a well-governed data asset and a well-intentioned hack. * Understanding of data pipeline concepts — ingestion, transformation, modeling, governance, delivery — sufficient to write clear product requirements and hold engineering accountable. Supply Chain Domain Knowledge * Working familiarity with at least two of the following Supply Chain domains: inventory management, order management, sourcing, or warehouse/fulfillment operations. Familiarity with adjacent domains — product creation/PLM or merchandise planning — is a plus but not required. * Understands the functional context behind supply chain data — what an OTIF metric means to an operations team, how a bill of materials drives production planning, why inventory position data needs to be real-time versus batch — and uses that context to prioritize and enrich data products. * Experience working in environments undergoing major ERP or platform transformation, where data assets must evolve in step with source system changes. Technical Acumen * Proficient in SQL and comfortable independently exploring data to validate product decisions and identify quality issues. * Working knowledge of data warehouse concepts, dimensional modeling, ETL/ELT patterns, and event-driven data flows. * Familiar with cloud data platforms (Snowflake preferred) and observability tooling for data pipelines. * Experienced with Agile/Scrum and tools such as Jira and Confluence. Able to assess technical trade-offs and guide teams toward sound architectural decisions. Communication & Influence * Exceptional written and verbal communicator — able to translate complex data concepts into business value for non-technical stakeholders and precise product requirements for engineering. * Skilled at building consensus across diverse stakeholder groups and influencing priorities without direct authority. * Comfortable presenting data strategy and product roadmaps to senior and executive audiences. Why This Role This is a rare opportunity to build something genuinely foundational, the governed, AI-ready data product layer that will power Fanatics' supply chain intelligence for years to come. You will work at the intersection of a major enterprise transformation and the frontier of AI-driven analytics, with the autonomy to define the approach and the stakeholder access to make it real. The scale is real. The problem is hard. And the impact on how Fanatics makes decisions, deploys AI, and runs its supply chain, will be visible across the entire organization. Where you’ll work and what's required * Office locations: Atlanta, GA or Boulder, CO * Hybrid work environment flexibility, working 3 days in office, 2 days remote weekly * Ability to travel for partner meetings, events, and other related activities. Why Fanatics * You will be building something that matters, the integration platform backbone behind the world's most passionate fan community. * The scale is real, a global operation spanning eCommerce, wholesale, and in-venue retail, with a partner network that continues to grow. * You will work alongside a talented, experienced team of engineers, operators, and product leaders who are deeply energized in getting this right. * Above all, you'll have fun doing it, building industry-defining integration capabilities alongside some of the best people in the business. * Competitive compensation, comprehensive benefits, and the chance to wear some very good kit. At Fanatics, we value transparency and honesty. If you don’t meet every single requirement, that’s okay – we still want to hear from you! We believe in the power of diverse experiences and talents. If you’re excited about the role and confident that you can contribute, don’t hesitate to apply. We’re genuinely interested in how your unique skills and perspective can help us build something amazing together. The salary range for this position is $188,000 - $250,000 which represents base pay only and does not include short-term or long-term incentive compensation. When determining base pay, as part of a final compensation package, we consider several factors such as location, experience, qualifications, and training. What's in it for you Culture: Join a team where you're surrounded by top-tier talent, driven by a shared passion to relentlessly enhance the fan experience. With a focus on collaboration, support, and continuous development, you’ll be empowered to help shape a our culture that celebrates both individual and team successes. Benefits: We provide a wide range of health, financial, legal, and development assistance, including wellness programs with fitness and weight management partners, paid maternity paternity leave, and infertility treatment. Additionally, we offer flexible time off to help you recharge, along with a competitive 401k plan to support your financial future. At Fanatics, we’re dedicated to supporting you in all aspects of work and life. Fanatics is building a leading global digital sports platform. We ignite the passions of global sports fans and maximize the presence and reach for our hundreds of sports partners globally by offering products and services across Fanatics Commerce, Fanatics Collectibles, and Fanatics Betting & Gaming, allowing sports fans to Buy, Collect, and Bet. Through the Fanatics platform, sports fans can buy licensed fan gear, jerseys, lifestyle and streetwear products, headwear, and hardgoods; collect physical and digital trading cards, sports memorabilia, and other digital assets; and bet as the company builds its Sportsbook and iGaming platform. Fanatics has an established database of over 100 million global sports fans; a global partner network with approximately 900 sports properties, including major national and international professional sports leagues, players associations, teams, colleges, college conferences and retail partners, 2,500 athletes and celebrities, and 200 exclusive athletes; and over 2,000 retail locations, including its Lids retail stores. Our more than 22,000 employees are committed to relentlessly enhancing the fan experience and delighting sports fans globally. Fanatics Commerce is a leading designer, manufacturer, and seller of licensed fan gear, jerseys, lifestyle and streetwear products, headwear, and hardgoods. It operates a vertically-integrated platform of digital and physical capabilities for leading sports leagues, teams, colleges, and associations globally – as well as its flagship site, www.fanatics.com. Fanatics Commerce has a broad range of online, sports venue, and vertical apparel partnerships worldwide, including comprehensive partnerships with leading leagues, teams, colleges, and sports organizations across the world—including the NFL, NBA, MLB, NHL, MLS, Formula 1, and Australian Football League (AFL); the Dallas Cowboys, Golden State Warriors, Paris Saint-Germain, Manchester United, Chelsea FC, and Tokyo Giants; the University of Notre Dame, University of Alabama, and University of Texas; the International Olympic Committee (IOC), England Rugby, and the Union of European Football Associations (UEFA). At Fanatics Commerce, we infuse our BOLD Leadership Principles in everything we do: · Build Championship Teams · Obsessed with Fans · Limitless Entrepreneurial Spirit · Determined and Relentless Mindset

Responsibilities

Own the product vision and execution for treating enterprise supply chain data as a managed asset to power human analytics and AI-driven workloads. Define and govern a shared data product layer and ensure data assets are AI-ready and decision-grade across multiple supply chain domains.