Lead the architecture, design, and implementation of Databricks-based data platforms, pipelines, and AI/ML workloads. • Define scalable lakehouse patterns using core Databricks capabilities such as Apache Spark, Delta Lake, Databricks SQL, MLflow, and governance components. • Design robust batch and streaming data pipelines for high-volume, business-critical workloads. • Establish architecture standards for performance optimization, workload orchestration, reliability, observability, and cost control. • Translate business and technical requirements into solution blueprints, reference architectures, and implementation roadmaps. • Collaborate with data engineers, analysts, data scientists, Dev Ops teams, and business stakeholders to deliver end-to-end solutions. • Ensure strong data governance, security, and compliance practices across the Databricks environment. • Support AI and advanced analytics use cases by enabling reliable feature engineering, model lifecycle practices, and prod...