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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. Data Engineer III About the Role We re looking for a Data Engineer III to join our Data Engineering team, which builds and governs the data foundation that powers the business. You ll work within our stack — Python ingestion pipelines, Airflow orchestration, and Snowflake/Databricks — helping move data reliably and securely from source to decision-ready output. You ll implement features and fixes against a given design, handle known classes of pipeline issues on your own, and escalate genuinely novel problems with clear context rather than working them in isolation. You re also expected to start contributing meaningfully in code review — catching real bugs, not just style nits. What You ll Do • Implement new ingestion sources end-to-end against a senior engineer s design — connector code, DAG, schema, monitoring, and catalog registration — extending the team s existing framework where a new source needs a pattern it doesn t yet support • Investigate pipeline failures independently, recognize known classes of issues, and ship the documented fix without needing to escalate • Before shipping a new pipeline, identify downstream consumers and what would break if data were late or wrong, and flag gaps like this during spec review — before writing code • Write clear handovers when escalating a genuinely unresolved issue — what you tried, what you ruled out, and where things diverge — so a senior can pick up without re-discovery • Review peers pipeline PRs and catch non-obvious issues (e.g., missing idempotency checks, race conditions) that could cause incorrect downstream data • Turn ambiguous "why is this data wrong?" questions into structured investigations — tracing data lineage from source to warehouse and communicating back what you found • Surface concerns in spec review as specific, well-reasoned questions rather than staying silent or blocking progress • Support data security and governance work (e.g., PII masking, access controls) and contribute to data delivery work, including reverse ETL integrations • Build strong working relationships with internal stakeholders and help scope and clarify

Data Engineer III - FMX

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