Take ownership of large portions of the dbt project (3k+ models, custom macros, tests), ensuring scalability, maintainability, and adherence to best practices
Design and implement robust data models using dimensional modeling, incremental strategies, and Slowly Changing Dimensions (SCDs)
Establish and enforce dbt test coverage, automated quality checks, and CI/CD pipeline standards (GitHub Actions)
Profile and optimize SQL queries and warehouse performance, focusing on efficiency and cost reduction
Build and refine the semantic layer, ensuring consistent business logic across Looker, Redash, and downstream tools
Collaborate with analysts and business partners to define metrics and deliver self-serve data assets
Document models, lineage, and transformation logic to make data discoverable and usable across the company
Contribute to shaping team standards and playbooks and stay ahead of modern data stack innovations
Design data models for self-service, prepare AI-ready data foundations, and partner with data science & ML teams
Requirements
3–5 years of experience in analytics engineering roles