• 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.