• Define and execute data platform strategy through a 2-3 year roadmap that unifies architecture, minimizes tech sprawl, and integrates with our marketplace replatforming (evolving from monolith to microservices). • Establish enterprise data quality standards by overhauling governance frameworks, metadata management, and compliance protocols (e.g. GDPR/CCPA) to rebuild trust in data assets. • Implement business data modeling practices by developing canonical models, semantic layers, and business glossaries that accurately reflect our operating environment, supported by governance and stakeholder education. • Operate all core data platforms including our Data Hub (employing the Medallion architecture), Events Platform (e.g. Kafka/Rudderstack), and AI/ML infrastructure, ensuring reliability, cost efficiency, and real-time capabilities. • Enable AI/ML adoption across teams by building platform capabilities (feature stores, model pipelines) while maintaining governance – without direct model development. • Activate data for business impact in partnership with the Director of Analytics, creating single-source-of-truth metrics and self-service tooling for Product, Growth, Finance, and Operations. • Lead 20+ engineers across 6 functional teams through mentorship, talent development, and cross-functional collaboration to scale our data practice.