• Lead the design and implementation of shared, reusable data models, defining shared fact tables, conformed dimensions, and a semantic/metrics layer that serves as the single source of truth across analytics functions • Drive standardization of data engineering practices across ADE and functional analytics teams, including pipeline patterns, CI/CD workflows, naming conventions, and data modeling standards • Partner with Data Infrastructure to modernize orchestration, improve pipeline decomposition, and establish secure dev/test environments with production data access • Architect and implement a shift-left data governance strategy, working with upstream data producers to establish data contracts, SLOs, and code-enforced quality gates that catch issues before production • Collaborate with Data Science leads and Product Management to translate metric definitions into reliable, certified data pipelines that power executive dashboards, WBR reporting, and growth measurement • Reduce operational burden by improving pipeline granularity, observability, and failure recovery, establishing runbooks and alerting standards that make on-call sustainable • Evaluate and integrate AI-native tooling into the data development lifecycle, enabling conversational data exploration with guardrails and AI-assisted pipeline development