Staff Data Engineer

Fanatics Betting & Gaming; Oregon; Híbrido; USD 181.000 - 238.000; Jornada completa

Descripción de la vacante

Fanatics Betting and Gaming is seeking a Staff Data Engineer to lead the data engineering stack, focusing on Python ingestion pipelines, Airflow orchestration, and Snowflake/Databricks. You will own architecture, define standards, and tackle high‑stakes problems that require scalable, secure, and cost‑effective data movement.

You will mentor engineers, drive reliability, and partner with BI, Data Science, Product, and compliance teams to turn ambiguous requirements into scalable solutions.

Formación

• 8+ years of professional software or data engineering experience.
• Track record of designing and delivering large cross‑team data systems.
• Expert‑level Python and SQL, with ETL/ELT experience.

Responsabilidades

• Own ingestion pipelines, orchestration, and data delivery systems.
• Lead architecture and design reviews for data platforms.
• Set reliability standards and reduce operational toil.
• Mentor engineers and collaborate with BI, Data Science, and Product teams.

Conocimientos

Python

SQL

Airflow

Snowflake

Data governance

Herramientas

Databricks

dbt

Tableau

PostgreSQL

MongoDB

AWS

Descripción del empleo

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

Launched 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.

About the Role

We’re looking for a Staff Data Engineer to join our Data Engineering team, which builds and governs the data foundation that powers the business. You’ll set technical direction for our stack (Python ingestion pipelines, Airflow orchestration, and Snowflake/Databricks) and make sure data moves reliably, securely, and cost-effectively from source to decision-ready output.

This is a senior individual-contributor role with broad scope and influence. You’ll own the architecture of our most critical data systems, define the standards the team builds against, and take on novel, ambiguous, high-stakes problems that don’t have a runbook. You’ll be accountable for outcomes, not just deliverables.

Responsibilities

• Own the architecture and design of ingestion pipelines, orchestration frameworks, and data delivery systems, producing design docs that DE2s, DE3s, and senior engineers can implement against
• Define and evolve the team’s frameworks, conventions, and reference patterns for pipelines, Airflow DAGs, testing, monitoring, and catalog registration so new sources onboard quickly and consistently
• Lead diagnosis of the novel data integrity, performance, and reliability problems that escape past senior engineers, driving systemic fixes and turning recurring failures into runbooks, automation, or better design
• Set and track reliability standards (SLOs, alerting, on-call health) and reduce operational toil
• Lead data security and governance strategy, including PII masking, RBAC, data classification, and lineage, in partnership with Security, Legal, and Compliance
• Design reverse ETL and data delivery integrations (e.g., Segment, LaunchDarkly, Kafka, S3) with clear SLAs, downstream-impact analysis, and failure-handling guarantees
• Drive platform decisions on Snowflake, Databricks, and AWS, including cost optimization, capacity planning, and build-vs-buy evaluation
• Lead spec and design review, anticipating downstream impact, race conditions, idempotency gaps, and failure modes before code is written, and review high-risk PRs with rigor
• Partner with BI, Data Science, Product, and business leadership to turn ambiguous requirements into scalable solutions, prioritize competing demands, and shape the roadmap
• Mentor engineers at every level, represent the team in cross‑functional forums, pay down technical debt, and participate in hiring

Experience and Skills

• 8+ years of professional software or data engineering experience, including significant experience owning production data platforms at scale
• A track record of designing and delivering large, cross‑team data systems from ambiguous requirements through production operation
• Expert‑level Python and SQL, with deep experience in ETL/ELT patterns for complex, high‑volume transformations
• Deep expertise in Airflow / Managed Workflows for Apache Airflow, including DAG design at scale and operational best practices
• Strong command of pipeline fundamentals: idempotency, backfills, schema evolution, late‑arriving data, data quality frameworks, and failure recovery
• Hands‑on experience with several of Snowflake, Databricks, AWS, dbt, Tableau, MongoDB, and PostgreSQL, with the judgment to choose the right tool for the job
• Experience building data security and governance capabilities (PII masking, RBAC, catalog/lineage) and reusable pipeline frameworks that other engineers extend
• Strong testing, CI/CD, and code review practices, and the ability to set those standards for a team
• Proven ability to mentor engineers, influence without authority, and build alignment across teams
• Excellent written and verbal communication, including design docs, tradeoff analysis, and incident write‑ups

Nice to Have

• Experience with reverse ETL, real‑time or streaming data (e.g., Kafka), and observability tooling (e.g., Datadog)
• Experience with FinOps and cost governance on cloud data platforms
• Background in gaming, betting, e‑commerce, or another regulated industry, including audit, compliance, and responsible handling of PII
• Experience leading platform migrations or major re‑architectures

Depending 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.

Ranges 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.

Salary Range

$180,500—$237,500 USD