{"id":3972979,"url":"https://alion.io/job/fanatics-data-engineer-ii","title":"Data Engineer II","company":{"id":1756301,"name":"Fanatics","domain":"fanatics.com","url":"https://alion.io/company/fanatics-com","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"A","score":87,"open_postings":12,"ghost_share":0,"stale_share":0.417,"repost_share":0.167,"time_to_fill_p50_days":42,"computed_at":"2026-11-09T06:03:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":118750,"max":156250,"currency":"USD","period":"year","gross":null,"usd_annual":156250},"salary_estimate":null,"experience_years_min":1,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"AWS","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Amazon S3","optional":true},{"name":"Apache Kafka","optional":true},{"name":"Datadog","optional":true}],"status":"live","first_seen_at":"2026-11-09T16:28:54Z","employer_posted_date":"2026-11-09","last_verified_at":"2026-11-09T16:54:29Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"About Us\nFanatics 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. \nAbout the Team\nLaunched in 2021, Fanatics Betting and Gaming is the online and retail sports betting subsidiary of Fanatics, a global digital sports platform. The Fanatics Sportsbook is available to 95% of the addressable online sports bettor market in the U.S. Fanatics Casino is currently available online in Michigan, New Jersey, Pennsylvania and West Virginia. Fanatics Betting and Gaming operates twenty-two retail sports betting locations, including the only sportsbook inside an NFL stadium at Northwest Stadium. Fanatics Betting and Gaming is headquartered in New York with offices in Denver, Leeds and Dublin.\nAbout the Role\nWe're looking for a Data Engineer II 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 execute well-defined tasks under the direction of senior data engineers, learn our team's stack and conventions, and build a strong foundation in pipeline correctness. You're not expected to own designs independently yet - you're expected to build reliable software against a design, ask good questions, and grow quickly from feedback.\nResponsibilities\nImplement ingestion pipelines and Airflow DAGs from a senior engineer's design, using the team's scaffolding and conventions - including writing the code, unit tests, and documentation\nSupport data security and governance work, such as PII masking and access controls, following established patterns\nContribute to data delivery work, including reverse ETL integrations, under guidance from senior engineers\nAdd and extend fields in existing pipelines, incorporating review feedback and applying learned patterns on future work\nTake oncall pages for pipeline failures, work through runbooks, and escalate with clear context when needed\nPair with senior engineers on data integrity issues you can't yet diagnose alone\nWrite clear, reviewer-friendly PR descriptions and ask clarifying questions before starting new work\nFlag blockers early and with context rather than going quiet when stuck\nBuild strong working relationships with internal stakeholders (BI analysts, other data engineers, data scientists) and help gather and clarify requirements\nConduct and participate in code and system inspections\nHelp the team define and adhere to data engineering best practices\nMentor more junior data engineers as you grow into the role\nExperience and Skills\n1-3 years of professional software or data engineering experience\nA self-learner with a strong ability to gather, evaluate, and analyze requirements\nSolid foundation in Python and deep understanding of SQL and ETL/ELT for complex data transformations\nComfort reading and writing unit tests, and working within an established codebase and conventions\nFamiliarity with (or eagerness to quickly learn) workflow orchestration tools like Airflow (Managed Workflows for Apache Airflow)\nBasic understanding of data pipeline concepts: ingestion, idempotency, scheduling, and data quality\nKnowledge of several of the following technologies: Snowflake, Databricks, AWS, dbt, Tableau, MongoDB, PostgreSQL\nFamiliarity with Git-based version control and PR-based code review workflows\nStrong communication skills - asks clarifying questions, writes clear PR descriptions, and escalates blockers with useful context rather than staying stuck silently\nA growth mindset: takes review feedback well, improves processes, and champions best practices to avoid technical debt\nNice to Have\nExposure to cloud data warehouses/lakehouses (Snowflake, Databricks, AWS) and data catalog/lineage tooling\nFamiliarity with dbt, Tableau, MongoDB, or PostgreSQL\nFamiliarity with reverse ETL tools or patterns (e.g., Segment, LaunchDarkly, Kafka, S3-based delivery)\nExposure to PII masking, data security, or RBAC/access governance concepts\nExposure to observability/monitoring tooling (e.g., Datadog) for pipeline health and alerting\nBackground in gaming, betting, e-commerce, or another regulated/high-compliance industry\nFamiliarity with responsible handling of customer/PII-sensitive data\nDepending on the role, your interview and onboarding experience may include in-person components, such as onsite interviews or Launching into Better: LIVE-a multi-day cultural immersion in New York City for full-time, non-seasonal hires. These sessions are designed to build connection and bring our culture to life, though specific travel and participation requirements will be confirmed based on your role and location. Your recruiter will provide clear guidance at each stage of the process.\nFor information about our benefits, please visit https://benefitsatfanatics.com/\n#LI-AL1 \nRanges will change based on country and state of residence, which are reflected in Geographical Zones defined by Fanatics Betting and Gaming. The range incorporates all of our Geographical Compensation Zones and is subject to change as the Zone associated with the actual offer is confirmed. In addition to the base and bonus, full-time employment, and more. For information about our benefits, please visit https://benefitsatfanatics.com/\nSalary Range\n$118,750—$156,250 USD\nBy submitting your application, you agree to our terms of service and acknowledge you have read our Candidate Privacy Policy.\nFanatics will never ask candidates for money, banking information, or other sensitive personal information as part of the interview process. 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