Roro Zoro

I’m a Data Engineer with 4 years of experience designing and optimizing scalable data pipelines using PySpark, Databricks, AWS, and the Hadoop ecosystem. I focus on ETL modernization, distributed data processing, and building cloud-native data engineering solutions that are dependable in production.

I’ve automated migration of legacy SQL workloads into reusable PySpark frameworks and built Delta Lake-based architectures. At Barclays, I developed and optimized PySpark pipelines for enterprise banking control frameworks, implementing validation controls, reusable ETL components, and efficient Spark partition strategies.

I also prioritize operational excellence: I’ve implemented centralized logging and monitoring with AWS CloudWatch, orchestrated end-to-end ETL with AWS Lambda/Glue/Step Functions, and strengthened reliability through resilience testing (AWS Fault Injection Simulator). From Capgemini to Barclays, I’ve supported production deployment and cutover activities with zero critical production incidents during release cycles.