AWS Databricks Architect

Architecture & Design Define and design end-to-end data lakehouse architecture leveraging Databricks, Delta Lake, and cloud-native services. Create reference architectures for batch, real-time, and streaming data pipelines . Architect data ingestion, curation, storage, and governance frameworks . Ensure the platform is scalable, secure, and optimized for performance and cost . Establish standards for data lineage, metadata management, and compliance . Work with enterprise architects to align Databricks solutions with overall cloud strategy (AWS). Leadership & Delivery Lead and mentor a team of data engineers in building robust data pipelines. Collaborate with data scientists, BI teams, and business stakeholders to enable advanced analytics and AI/ML use cases. Drive adoption of DevOps and CI/CD practices for data engineering. Review designs and solutions to ensure adherence to architectural principles. Implementation & Optimization Build, optimize, and manage large-scale PySpark/SQL pipelines in Databricks. Enable real-time data processing through Kafka, Kinesis, or Event Hubs . Implement security best practices including RBAC, data masking, and encryption.