I've built scalable data pipelines and dimensional data models at Egen and Johnson Controls, enabling fraud reporting, analytics, and reliable workflows across large datasets.
At Johnson Controls, I developed Python, Spark, and SQL pipelines on GCP, automated workflows with Airflow, and reduced BigQuery backup storage needs by 10x through compression. I also migrated legacy processes to scalable cloud architecture on Azure at Egen.
I've applied machine learning and generative AI at Encyclopedia Britannica and Reliance Jio, including NLP extraction across 130k+ articles and a SparkML sentiment pipeline with 86% accuracy. I bring hands-on experience across AWS, GCP, Azure, BigQuery, Spark, Kafka, and modern data warehousing.
