Staff Data Engineer

Fanatics Betting & Gaming; United States; In loco; USD 180.000 - 280.000; Tempo pieno

Descrizione del lavoro

Fanatics Betting & Gaming seeks a Staff Data Engineer to lead our data engineering team, shaping the data foundation that powers decision-making. You will own ingestion pipelines, orchestration, and data delivery, balancing reliability, security, and cost efficiency at scale.

You will mentor engineers, define standards for pipelines, and drive architecture decisions across Snowflake, Databricks, and AWS, partnering with BI, Data Science, and product leadership to turn ambiguous needs into

Competenze

• 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.

Mansioni

• 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 escal
• 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

Conoscenze

Python

SQL

ETL/ELT

Airflow

Data pipelines

Technical leadership

Strumenti

Snowflake

Databricks

AWS

dbt

Tableau

MongoDB

PostgreSQL

Descrizione del lavoro

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 escal
• 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 Postgre