Designs, builds, and maintains scalable batch and streaming data pipelines across AWS and GCP. Develops ETL/ELT workflows using Python, PySpark, and advanced SQL; optimizes performance, storage, and query execution; implements data quality and governance controls; and supports data lakes, warehouses, and ML workflows. Collaborates with data scientists and ML engineers on MLOps automation and production deployments while maintaining CI/CD, Docker, infrastructure standards, and technical documentation.