[Hiring] Data Engineer II @Fanatics Betting & Gaming

Role Description

We'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.

Responsibilities

• Implement 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.
• Support data security and governance work, such as PII masking and access controls, following established patterns.
• Contribute to data delivery work, including reverse ETL integrations, under guidance from senior engineers.
• Add and extend fields in existing pipelines, incorporating review feedback and applying learned patterns on future work.
• Take oncall pages for pipeline failures, work through runbooks, and escalate with clear context when needed.
• Pair with senior engineers on data integrity issues you can't yet diagnose alone.
• Write clear, reviewer-friendly PR descriptions and ask clarifying questions before starting new work.
• Flag blockers early and with context rather than going quiet when stuck.
• Build strong working relationships with internal stakeholders (BI analysts, other data engineers, data scientists) and help gather and clarify requirements.
• Conduct and participate in code and system inspections.
• Help the team define and adhere to data engineering best practices.
• Mentor more junior data engineers as you grow into the role.

Qualifications

• 1–3 years of professional software or data engineering experience.
• A self-learner with a strong ability to gather, evaluate, and analyze requirements.
• Solid foundation in Python and deep understanding of SQL and ETL/ELT for complex data transformations.
• Comfort reading and writing unit tests, and working within an established codebase and conventions.
• Familiarity with (or eagerness to quickly learn) workflow orchestration tools like Airflow (Managed Workflows for Apache Airflow).
• Basic understanding of data pipeline concepts: ingestion, idempotency, scheduling, and data quality.
• Knowledge of several of the following technologies: Snowflake, Databricks, AWS, dbt, Tableau, MongoDB, PostgreSQL.
• Familiarity with Git-based version control and PR-based code review workflows.
• Strong communication skills — asks clarifying questions, writes clear PR descriptions, and escalates blockers with useful context rather than staying stuck silently.
• A growth mindset: takes review feedback well, improves processes, and champions best practices to avoid technical debt.

Nice to Have

• Exposure to cloud data warehouses/lakehouses (Snowflake, Databricks, AWS) and data catalog/lineage tooling.
• Familiarity with dbt, Tableau, MongoDB, or PostgreSQL.
• Familiarity with reverse ETL tools or patterns (e.g., Segment, LaunchDarkly, Kafka, S3-based delivery).
• Exposure to PII masking, data security, or RBAC/access governance concepts.
• Exposure to observability/monitoring tooling (e.g., Datadog) for pipeline health and alerting.
• Background in gaming, betting, e-commerce, or another regulated/high-compliance industry.
• Familiarity with responsible handling of customer/PII-sensitive data.

Salary Range

$118,750 — $156,250 USD

Additional Information

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