Staff Data Analyst
Fanatics Betting & Gaming · United States
About Us 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. Overview You own the data foundation behind how CX Operations understands its performance and how it connects to the broader Fanatics ecosystem. As the Staff Analyst for Ops Ecosystem Analytics, you design and build the architecture, models, and operating standards that make CX Ops ecosystem data in Snowflake trustworthy, scalable, and usable by cross-functional teams, leaders, and by the AI agents we're building on top of it. This is a hands-on technical role with broad influence. You take raw tables from across the business and turn them into clean, documented, tested models that the rest of the team builds on. You work side by side with Data & Analytics Engineering as well as Strategy teams. You set the SQL and data-modeling bar for the Ops Analytics team without managing anyone. You tell the story of what the data says, regularly presenting to senior leadership and translating architecture decisions and analytical findings into impact they can act on. We are building toward an AI-first way of operating, and this role is central to it. The right person is technically sharp, relentlessly detail-oriented, and curious about both what the data is saying and how AI changes the way we find and act on answers. You move fast, own ambiguous problems, and hold yourself to a high bar without being told to. What You'll Do Data architecture and operations environment Own the architecture of CX Ops ecosystem data in Snowflake, including schema design, data layers, access patterns, and the operating model that keeps it reliable as it scales. Decide how ecosystem Ops data should be structured, owned, and governed, and drive alignment with necessary teams, like Data Engineering, on those decisions. Consolidate overlapping or one-off datasets into shared, well-governed sources of truth, and set naming and documentation conventions. Define and track data quality standards for Ops ecosystem data. Build alerting on critical metrics as needed so issues are caught before they reach leadership reporting. dbt and analytics engineering Turn raw cross-domain tables into clean, tested, reusable dbt models that the whole team can build on. Own the team's core models and introduce data tests, code review practices, and modeling standards that catch issues before they reach stakeholders. Review teammates' SQL, models, and dashboards for correctness, performance, and readability, and coach analysts on best practices. Replace manual, one-off data pulls with automated, always-on solutions. Analytical work and insights Lead complex, cross-functional analyses from an ambiguous business problem through scoping, analysis, and a decision-ready recommendation, without formal authority over contributors. Diagnose root causes rather than symptoms,