Lead and develop Analytics Engineers responsible for shared data foundations, platform capabilities, semantic models, developer tooling, and AI-enabled workflows. Define the team vision, operating model, roadmap, standards, and success measures. Partner cross-functionally to prioritize initiatives, improve adoption, guide architecture, and deliver scalable data assets and automation. Drive responsible AI-assisted development, data reliability, testing, documentation, observability, and cost management while contributing hands-on when needed.

Manage and mentor a data engineering team while leading Snowflake-based platform architecture, enterprise data integrations, governance, observability, and pipeline reliability. Partner with analysts, business leaders, product management, and engineering teams to improve trusted self-service data access. Establish engineering standards, modernize the data stack, optimize costs, and deliver an AI-ready data foundation supporting analytics, reporting, and future AI initiatives.

Own the strategy, governance, architecture, modeling, and reporting foundation for People Experience data. Build governed metrics, semantic and consolidated data layers, dashboards, data catalogs, quality monitoring, and operating processes from the ground up. Manage intake, prioritization, access, privacy, enablement, and self-service adoption while partnering with stakeholders on analytics and future AI capabilities. The role combines strategic program leadership with hands-on SQL, data modeling, reporting, and team mentoring.