Build and maintain large-scale data warehouses, data marts, and transformation pipelines using Python, SQL, Snowflake, and dbt. Make data accessible and actionable for product and business decision-making, optimize query and table performance, implement data quality testing and monitoring, and partner with engineering, analytics, data science, product, and business stakeholders. Mentor teams on data best practices and use AI tools to improve workflows.

Designs and owns scalable data architecture, pipelines, models, visualizations, integrations, and governance for customer-facing and business data products. Collaborates with engineering, product, and data science teams; manages data SLAs, security, privacy, quality, and reliability. Optimizes production systems and ETL processes, supports structured and unstructured data, mentors team members, and participates in evening availability as needed.