• Design, implement, and maintain complex data pipelines, ensuring scalability and reliability using Airflow, dbt, Rivery, Python, and SQL, enabling robust ingestion and transformation of structured and semi-structured data. • Serve as a strategic partner to business teams, working closely with stakeholders to translate high-level goals into data solutions that support forecasting, performance tracking, and optimization. • Develop and maintain clean, well-documented data models in Snowflake and BigQuery that support analytics, reporting, and operational workflows and contribute to architecture decisions. • Integrate data from a variety of internal and external sources, including Google Analytics and third-party APIs, to support full-funnel visibility across departments. • Enable self-service analytics by ensuring data assets are discoverable and usable via tools such as Tableau, including thoughtful semantic layer design and performance tuning. • Contribute to the development of robust monitoring and observability practices for data quality and pipeline health. • Collaborate on architecture and design decisions, including cloud infrastructure and containerization using AWS, Pulumi, and Docker. • Maintain strong documentation and promote engineering standards that ensure transparency, maintainability, and reusability of data systems.