[Remote] Data Engineer II

Note: The job is a remote job and is open to candidates in USA. Fanatics Betting and Gaming is hiring a Data Engineer II to help build and govern the data foundation that powers its business. The role implements and supports reliable data pipelines, orchestration, security, governance, and data delivery while working from established designs and collaborating with senior engineers and internal stakeholders.

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

Skills

• 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
• 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

Company Overview

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