Responsibilities 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, DevOps 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 pr...