Senior Analytics Engineer

Underdog is a rapidly growing sports company focused on creating fun products for sports fans. As a Senior Analytics Engineer, you will play a crucial role in building and maintaining data models that influence business strategy and product innovation.

Responsibilities:

• Build and maintain core dbt data models that turn raw data into clean, trusted, analysis-ready assets (e.g., User 360, Contest Fact, Marketing Attribution)
• Implement and manage a semantic layer (dbt MetricFlow, Omni, or equivalent) to standardize definitions of key metrics across the company
• Own data quality and reliability, setting up automated testing, monitoring, and alerting frameworks
• Collaborate with analysts and data scientists across Product, Marketing, Finance, and Ops to understand needs and deliver data models that scale
• Contribute to self-service analytics enablement by making models discoverable in tools like Omni, Hex, and Sigma, and building user-friendly dashboards and explores
• Champion software engineering best practices in analytics: Git workflows, code review, CI/CD for dbt, and reusable SQL patterns
• Document business logic and metric definitions in a central data catalog, ensuring clarity and consistency

Requirements:

• SQL and data modeling expert, with 4+ years in analytics engineering, BI, or related data roles
• Skilled in dbt and modern cloud data warehouses (Snowflake, BigQuery, Databricks)
• Experienced with semantic layers and BI tools (Omni, Looker, Sigma, Hex) to drive metric consistency
• Comfortable with orchestration tools (Airflow, Dagster, Prefect) and Git-based workflows
• Detail-oriented with a passion for data quality and reliability
• Strong communicator who can translate complex data models into clear, actionable insights for technical and non-technical partners
• Collaborative teammate with a bias for action, comfortable in a fast-paced startup environment
• Build and maintain core dbt data models that turn raw data into clean, trusted, analysis-ready assets (e.g., User 360, Contest Fact, Marketing Attribution)
• Implement and manage a semantic layer (dbt MetricFlow, Omni, or equivalent) to standardize definitions of key metrics across the company
• Own data quality and reliability, setting up automated testing, monitoring, and alerting frameworks
• Collaborate with analysts and data scientists across Product, Marketing, Finance, and Ops to understand needs and deliver data models that scale
• Contribute to self-service analytics enablement by making models discoverable in tools like Omni, Hex, and Sigma, and building user-friendly dashboards and explores
• Champion software engineering best practices in analytics: Git workflows, code review, CI/CD for dbt, and reusable SQL patterns
• Document business logic and metric definitions in a central data catalog, ensuring clarity and consistency
• Experience in the sports, fantasy, or gaming industry
• Background in real-time or streaming analytics
• Contributions to the dbt community or open-source analytics projects
• Familiarity with data observability platforms (Monte Carlo, Elementary)