Data Pipeline Migration: Led the successful migration of an entire data pipeline, along with all dependencies, from Azure Databricks to Snowflake. This transition resulted in a 34% increase in annual revenues and improved performance by 20%.License Usage Analytics: Developed robust data pipelines for product license usage analytics, providing deeper insights into product consumption and identifying upsell opportunities. Analyzed customer usage patterns, leading to a 20% increase in customer engagement and a 15% increase in sales opportunities.

Data Pipelines for Analytics: Designed and implemented complex data pipelines for product feature usage analytics, providing actionable insights that led to a 25% increase in user engagement and a 15% improvement in feature adoption.Product Compatibility Analysis: Developed data pipelines to assess product compatibility with customer systems, enabling informed product change decisions. This proactive approach prevented potentially disruptive rollouts, sped up support case resolution, and reduced customer issues by 25%.

Implemented Databricks SQL: Evaluated and transitioned from a traditional SQL data warehouse to Databricks SQL, which accessed data directly from the Lakehouse. This move significantly reduced data duplication and annual data movement costs by 23%.Automation of Test Scripts: Worked closely with the QA Lead to automate daily test execution scripts, ensuring data reliability and consistency. Integrated the results with a reporting tool for visual analysis, saving the team 20 hours of manual work each week.