# Data - FMX at Fanatics ... [Fanaticsfbg](https://gurify.com/jobs?q=Fanaticsfbg) · London, United Kingdom · Posted yesterday [Apply on the original posting → (opens in a new tab)](https://job-boards.greenhouse.io/fanaticsfbg/jobs/4397142009) ## Job description ### 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. ### Software Engineer III - Data - FMX ### United Kingdom ### 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 requirements for new work - Mentor DE2s on their first significant projects — pairing on tricky decisions and helping them apply team conventions ### What We're Looking For - 3–5 years of professional software or data engineering experience - Strong SQL and Python skills, with solid experience building and operating production data pipelines - Comfort investigating and root-causing pipeline issues independently before escalating - Experience with workflow orchestration tools (Airflow or similar) and a cloud data warehouse/lakehouse (Snowflake, Databricks, or similar) - Solid understanding of data pipeline concepts: idempotency, schema evolution, backfills, and data quality/testing - Experience giving substantive code review feedback, not just style or formatting comments - Strong communication skills — can write a clear technical handover, ask sharp questions in spec review, and explain a data lineage investigation to a non-technical stakeholder - A track record of taking ownership of known-class problems end-to-end rather than needing step-by-step direction ### Nice to Have - Experience extending or building reusable pipeline frameworks/templates - Exposure to reverse ETL tools or patterns, PII masking, or data access governance (RBAC) - Exposure to observability/monitoring tooling (e.g., Datadog) for pipeline health and alerting - Some experience mentoring or informally supporting more junior engineers - Background in gaming, betting, e-commerce, or another regulated/high-compliance industry ### Why Join Us - Real ownership over known-class problems, with senior/staff support available for the genuinely novel ones - Work on high-visibility, high-trust systems that the business depends on - A culture built around clear tenets: standardize before you scale, own the outcome (not just the ticket), and clarity over complexity - Clear growth path into Senior Data Engineer, with room to start mentoring and shaping team practices along the way By submitting your application, you agree to our terms of service and acknowledge you have read our Candidate Privacy Policy. **Live in Fanaticsfbg’s hiring system.** Read from the company's own applicant tracking system, not reposted from a job board — so it's a real, open requisition rather than an ad that outlived the role. We remove it as soon as it disappears at source. ## More jobs like this - 9F [Senior Product Manager (Data APIs)](https://gurify.com/job/senior-product-manager-data-apis-at-9fin-8df4b0d55569) 9FIN · London · 5 days ago - 9F [Senior Product Manager (Data APIs)](https://gurify.com/job/senior-product-manager-data-apis-at-9fin-eeee125b3844) 9FIN · London · 5 days ago - DA [Solutions Architect (Presales, Data & AI, Digital Native Business)](https://gurify.com/job/solutions-architect-presales-data-ai-digital-native-business-at-2b32bb859961) Databricks · London, United Kingdom · 5 days ago - PL [Senior Program Manager, Professional Services ...](https://gurify.com/job/senior-program-manager-professional-services-at-planetlabs-ab481e6e4bbc) Planetlabs · London, United Kingdom · last week - EN [Human Data Program Manager](https://gurify.com/job/human-data-program-manager-at-encord-ff0127090438) Encord · London · last week - TO [Senior Director of Product, International - London, England, United ...](https://gurify.com/job/senior-director-of-product-international-london-england-united-at-993f761c4235) Toast · London, United Kingdom · last week ```json {"@context":"https://schema.org/","@type":"JobPosting","title":"Data - FMX at Fanatics ...","description":"\u003Ch3\u003EAbout Us\u003C/h3\u003E\u003Cp\u003EFanatics 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 \u0026amp; 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.\u003C/p\u003E\u003Ch3\u003ESoftware Engineer III - Data - FMX\u003C/h3\u003E\u003Ch3\u003EUnited Kingdom\u003C/h3\u003E\u003Ch3\u003EAbout Us\u003C/h3\u003E\u003Cp\u003EFanatics 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 \u0026amp; 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.\u003C/p\u003E\u003Ch3\u003EData Engineer III\u003C/h3\u003E\u003Cp\u003EAbout the Role\u003Cbr /\u003EWe\u0026#39;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\u0026#39;ll work within our stack \u2014 Python ingestion pipelines, Airflow orchestration, and Snowflake/Databricks \u2014 helping move data reliably and securely from source to decision-ready output.\u003Cbr /\u003EYou\u0026#39;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\u0026#39;re also expected to start contributing meaningfully in code review \u2014 catching real bugs, not just style nits.\u003C/p\u003E\u003Ch3\u003EWhat You\u0026#39;ll Do\u003C/h3\u003E\u003Cul\u003E\u003Cli\u003EImplement new ingestion sources end-to-end against a senior engineer\u0026#39;s design \u2014 connector code, DAG, schema, monitoring, and catalog registration \u2014 extending the team\u0026#39;s existing framework where a new source needs a pattern it doesn\u0026#39;t yet support\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EInvestigate pipeline failures independently, recognize known classes of issues, and ship the documented fix without needing to escalate\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EBefore 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 \u2014 before writing code\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EWrite clear handovers when escalating a genuinely unresolved issue \u2014 what you tried, what you ruled out, and where things diverge \u2014 so a senior can pick up without re-discovery\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EReview peers\u0026#39; pipeline PRs and catch non-obvious issues (e.g., missing idempotency checks, race conditions) that could cause incorrect downstream data\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003ETurn ambiguous \u0026quot;why is this data wrong?\u0026quot; questions into structured investigations \u2014 tracing data lineage from source to warehouse and communicating back what you found\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003ESurface concerns in spec review as specific, well-reasoned questions rather than staying silent or blocking progress\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003ESupport data security and governance work (e.g., PII masking, access controls) and contribute to data delivery work, including reverse ETL integrations\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EBuild strong working relationships with internal stakeholders and help scope and clarify requirements for new work\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EMentor DE2s on their first significant projects \u2014 pairing on tricky decisions and helping them apply team conventions\u003C/li\u003E\u003C/ul\u003E\u003Ch3\u003EWhat We\u0026#39;re Looking For\u003C/h3\u003E\u003Cul\u003E\u003Cli\u003E3\u20135 years of professional software or data engineering experience\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EStrong SQL and Python skills, with solid experience building and operating production data pipelines\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EComfort investigating and root-causing pipeline issues independently before escalating\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EExperience with workflow orchestration tools (Airflow or similar) and a cloud data warehouse/lakehouse (Snowflake, Databricks, or similar)\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003ESolid understanding of data pipeline concepts: idempotency, schema evolution, backfills, and data quality/testing\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EExperience giving substantive code review feedback, not just style or formatting comments\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EStrong communication skills \u2014 can write a clear technical handover, ask sharp questions in spec review, and explain a data lineage investigation to a non-technical stakeholder\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EA track record of taking ownership of known-class problems end-to-end rather than needing step-by-step direction\u003C/li\u003E\u003C/ul\u003E\u003Ch3\u003ENice to Have\u003C/h3\u003E\u003Cul\u003E\u003Cli\u003EExperience extending or building reusable pipeline frameworks/templates\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EExposure to reverse ETL tools or patterns, PII masking, or data access governance (RBAC)\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EExposure to observability/monitoring tooling (e.g., Datadog) for pipeline health and alerting\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003ESome experience mentoring or informally supporting more junior engineers\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EBackground in gaming, betting, e-commerce, or another regulated/high-compliance industry\u003C/li\u003E\u003C/ul\u003E\u003Ch3\u003EWhy Join Us\u003C/h3\u003E\u003Cul\u003E\u003Cli\u003EReal ownership over known-class problems, with senior/staff support available for the genuinely novel ones\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EWork on high-visibility, high-trust systems that the business depends on\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EA culture built around clear tenets: standardize before you scale, own the outcome (not just the ticket), and clarity over complexity\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EClear growth path into Senior Data Engineer, with room to start mentoring and shaping team practices along the way\u003C/li\u003E\u003C/ul\u003E\u003Cp\u003EBy submitting your application, you agree to our terms of service and acknowledge you have read our Candidate Privacy Policy.\u003C/p\u003E","identifier":{"@type":"PropertyValue","name":"Gurify","value":"data-fmx-at-fanatics-at-fanaticsfbg-c948458b267b"},"url":"https://gurify.com/job/data-fmx-at-fanatics-at-fanaticsfbg-c948458b267b","datePosted":"2026-09-07","validThrough":"2026-10-23T23:59:59Z","hiringOrganization":{"@type":"Organization","name":"Fanaticsfbg","sameAs":"https://job-boards.greenhouse.io/fanaticsfbg"},"directApply":false,"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressCountry":"GB","addressLocality":"London"}}} ``` ```json {"@context":"https://schema.org/","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Jobs","item":"https://gurify.com/jobs"},{"@type":"ListItem","position":2,"name":"United Kingdom","item":"https://gurify.com/jobs/united-kingdom"},{"@type":"ListItem","position":3,"name":"Data - FMX at Fanatics ...","item":"https://gurify.com/job/data-fmx-at-fanatics-at-fanaticsfbg-c948458b267b"}]} ```