• Design, develop, and maintain scalable batch and streaming data pipelines using PySpark, SQL, and modern data engineering frameworks • Perform deep-dive analysis into complex source systems to define extraction patterns, transformation logic, and integration workflows • Implement data models optimized for analytics, performance, and operational excellence • Build and manage data systems across AWS or GCP cloud environments, ensuring reliability, scalability, and cost efficiency • Lead and participate in design reviews, provide mentorship to junior engineers, and take ownership of code quality and engineering best practices • Collaborate with cross-functional teams including architects, analysts, product, and platform engineers to deliver high-quality data solutions • Troubleshoot performance bottlenecks, optimize data processing workflows, and improve pipeline robustness