• Developed and optimized frontend instrumentation and real-user monitoring (RUM) using Next.js, ensuring seamless tracking of user interactions while
• maintaining SSR (Server-Side Rendering) and SSG (Static Site Generation) performance.
• Integrated GraphQL APIs to efficiently fetch and aggregate real-time analytics data, reducing
unnecessary network requests and improving ad tracking precision.
• Implemented custom event tracking via Adobe Analytics (eVars & props), mapping raw data from
Kafka topics to structured frontend analytics variables.
• Engineered high-performance UI event listeners to capture user actions across Walmart’s international
platforms, enhancing ad performance measurement and attribution accuracy.
• Designed an automation pipeline to extract custom metrics from Adobe UI, transform the data, and push insights to AWS/GCP for a GenAI-powered ad optimization project.
• Optimized frontend performance and data collection efficiency, leveraging code splitting, lazy loading, and GraphQL query optimization to improve load times and scalability