• Own Databricks platform strategy: architecture decisions, Unity Catalog migration, cost optimization, and operational excellence. • Drive data pipeline development: real-time and batch pipelines using PySpark, Spark Structured Streaming, and Delta Lake. • Establish data quality standards: validation frameworks, monitoring, alerting, and SLA management. • Partner with Data Architects to translate Enterprise Data Models into performant physical implementations. • Integrate streaming infrastructure: Kafka-based event-driven ingestion and processing. • Build reporting capabilities: dashboards, KPIs, and self-service analytics for internal and client-facing use. • Drive data storytelling: executive presentations, client reporting, and strategic business insights. • Develop metrics frameworks: campaign performance, audience quality, and platform health KPIs. • Support ad-hoc analysis for campaign optimization and business questions. • Lead and grow DE and Analytics teams: hiring, mentoring, performance management, and career development. • Coordinate with offshore partners to extend team capacity and manage distributed development workflows. • Partner cross-functionally with Data Science, Product, and Client Success to align data capabilities with business needs. • Champion engineering best practices: code reviews, CI/CD, testing, documentation, and observability.