Sudip Padhye is a data engineer with nine years of experience building and automating scalable data pipelines and data quality frameworks for retail and logistics platforms. He has delivered production-grade solutions at Nordstrom and DoorDash, reducing redeployment time, minimizing errors, and improving data retrieval latency by combining Python and Go pipelines with Spark, Hive, Kafka and Airflow. Skilled in AWS orchestration and CI/CD for Kubernetes-based deployments, he also implemented anomaly detection and incident notification integrations with Slack, PagerDuty and email. A recognized subject-matter expert and conference speaker, Sudip pairs hands-on engineering with a pragmatic focus on observability and security. His academic background (MS in Data Science from Indiana University) complements practical ETL, SQL and Agile experience across enterprise-scale analytical platforms. Outside core duties he’s delivered creative value-adds like auto-archiving frameworks and RCA alerting that highlight his penchant for automating operational headaches.
9 years of coding experience
5 years of employment as a software developer
Bachelor of Engineering (B.E.), Computer Science & Engineering (CSE), Bachelor of Engineering (B.E.), Computer Science & Engineering (CSE) at Visvesvaraya Technological University
Master of Science - MS, Data Science, Master of Science - MS, Data Science at Indiana University Bloomington
Repository for the product solution provided by COVID Outbreak Detection Team 06.
Contributions:844 commits, 7 PRs, 813 pushes in 8 months
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