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.

About The Team

We're looking for an Analytics Engineer to join the Sales Finance Engineering team at Fanatics Collectibles. This team is the technical backbone for our Commercial, Sales, Strategy, and Finance organizations, and this role sits at the intersection of those business relationships and the data infrastructure that serves them via our internal applications. You'll spend roughly equal time understanding what our stakeholders need and building the systems that deliver it.

That means partnering directly with product managers, finance analysts, and sales ops leaders to translate fuzzy business questions into well-defined data products and then owning the pipeline, transformation, and visualization work that makes those products real. This isn't a pure platform engineering role or a pure analytics role.

Requirements

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into clear data specs and prioritized work, often without a fully formed brief to start from Communicate proactively with partners explaining tradeoffs, setting expectations, and making complex data concepts accessible Tag into broader engineering work on the Sales Finance team as needed this could mean contributing to data-oriented product features, reviewing code, or supporting integrations that touch our data layer What You'll Bring 3–5 years of experience in a analytics engineering, data engineering or software engineering, or a hybrid (preferred) Hands-on experience with Snowflake.

What You'Ll Do

Build and maintain data pipelines that bring data from source systems into Snowflake, with a focus on reliability, observability, and maintainability Implement and manage orchestration flows using Airflow or Dagster Build transformation layers using dbt, including data modeling, testing, and documentation standards Design and maintain Sigma dashboards that serve as the primary reporting surface for our business stakeholders Ensure data quality and consistency across reporting surfaces, establishing validation practices and source-of-truth definitions Partner with Commercial, Sales, Strategy, and Finance stakeholders, product manager and engineering leads to understand data and reporting needs, surface gaps, and build the tools necessary to support Translate business