Flipkart Accounting project:Developed a Python data pipeline to compare two Big Data report files from Google Cloud Storage (GCS) and identified discrepancies based on specific column valuesUtilized Pyspark for detailed data analysis, querying, and debugging to extract valuable insights.Led the creation and migration of dashboards, and developed team-specific portal summaries within the Metabase BI application for the internal Reconciliation platform Facilitated streamlined onboarding of various teams onto the Reconciliation platform(internal product), enabling seamless comparison of data report across different sources.Managed product demonstrations for the client team, enhancing their understanding and engagement with the platform builtDocumented the key features of the product in Confluence, including sections for 'Contact Us,' 'FAQ,' and initial troubleshooting steps.Flipkart Wholesale Credit platform:Led the automation and implementation of a retry mechanism for the stuck credit platform onboarding applications using Python, resulting in a 25% reduction in manual intervention during the onboarding process.Orchestrated the development and deployment of an alert generation system for un-relayed events across services using Python and shell scripting, managed through the Azkaban scheduler. This proactive approach enabled early identification of un-relayed data, minimized event mismatches across cross-functional teams, and ensured timely updates to user credit statusesEffectively managed ad hoc requests from business teams by utilizing SQL queries for precise data extraction, demonstrating strong problem-solving and data management skills.

Automated the package release build procedure using python and shell scripting and directly worked with Intel stakeholders