• Own data platform health and pipeline performance with defined SLAs (freshness, completeness, correctness) • Implement modern data observability (monitoring for volume anomalies, freshness gaps, schema changes, and pipeline failures) • Lead incident response and root-cause workflows, partnering with Engineering on cross-system fixes • Define scalable data architecture (warehouse/lakehouse/hybrid) and canonical, governed datasets • Own HIPAA-aware web & product analytics instrumentation, event taxonomy, and QA standards • Uplevel BI dashboard performance, segmentation, and metric governance (semantic layer, documented sources of truth, fast load times) • Provide technical leadership for customer data integrations, partnering daily with Customer Success, Data, and Engineering • Establish lightweight governance: metric definitions, access controls, documentation, and ownership • Mentor team members while shaping the future structure of the data & analytics function