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Tech-First Sports Licensed E-Commerce Cutting-Edge Company
The Role
Build and operate production data pipelines using Python, SQL, Airflow, Snowflake, and Databricks. Implement ingestion sources, DAGs, schemas, monitoring, catalog registration, reverse ETL, and governance controls. Investigate pipeline failures, perform lineage analysis, review code, identify downstream risks, and support data quality, security, and access controls. Collaborate with stakeholders, clarify requirements, document escalations, and mentor junior data engineers.
Summary Generated by Built In
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
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
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Skills Required
- 3-5 years of professional software or data engineering experience
- Strong SQL and Python skills
- Experience building and operating production data pipelines
- Experience with workflow orchestration tools such as Airflow or similar
- Experience with a cloud data warehouse or lakehouse such as Snowflake, Databricks, or similar
- Understanding of idempotency, schema evolution, backfills, and data quality/testing
- Experience providing substantive code review feedback
- Strong technical communication skills, including handovers, specification reviews, and data lineage explanations
- Track record of owning known-class problems end-to-end
- Experience extending or building reusable pipeline frameworks or templates
- Exposure to reverse ETL tools or patterns, PII masking, or data access governance such as RBAC
- Exposure to observability or monitoring tools such as Datadog
- Experience mentoring or informally supporting junior engineers
- Background in gaming, betting, e-commerce, or another regulated or high-compliance industry
Fanatics Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Fanatics and has not been reviewed or approved by Fanatics.
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Strong & Reliable Incentives — Incentives like annual bonuses and overtime opportunities are common, supporting higher total compensation especially in corporate roles. Seasonal premiums and performance bonuses are also cited across roles.
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Healthcare Strength — Multiple medical plan options, mental-health services, and wellness programs are highlighted as core offerings. Additional supports like HSAs/FSAs and condition management further strengthen the health package.
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Parental & Family Support — Paid maternity and paternity leave, fertility benefits, adoption assistance, and gender-affirmation coverage are explicitly included. Childcare support and backup care resources are also referenced.
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The Company
What We Do
Transforming the licensed sports industry through an innovative vertical e-commerce model that allows Fanatics to quickly design, manufacture and distribute high-quality fan gear across retail channels, better serving the real-time expectations of leagues, teams, fans and retailers in today’s mobile-first, on-demand culture.
Why Work With Us
You don't have to love sports to work here (though we love sports fanatics as well!). Fanatics is an industry leading, multi-billion dollar, international, privately held company with a casual, lofty space in the heart of Downtown Boulder. We have the advantages of a startup, without the pitfalls.
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