Experienced Data Engineer with 4 years building scalable data pipelines and real-time processing systems using Python, Spark, and Kafka. Proven success in delivering end-to-end ETL workflows on AWS and Snowflake for high-volume use cases in finance and insurance. At Sigmoid (Goldman Sachs project), automated risk reporting pipelines that improved visibility by 95% and prevented financial exposure. At Accenture, led a common data pipeline initiative using Kubernetes, Kafka, and Airflow—cutting execution time by 40% and increasing code reuse across teams. Certified in AWS and Apache Spark. Passionate about clean architecture, automation, and data-driven solutions.