I lead the development of the ThirdEye UI, an advanced tool designed for anomaly detection and root cause analysis, leveraging data visualization techniques. My key responsibilities and achievements include:

ThirdEye UI Development: Spearheading the development of ThirdEye UI, focusing on creating a user-friendly interface that enables anomaly detection and root cause analysis through data visualization methods. Collaborating closely with our designer, I actively contribute UX/UI ideas to enhance the overall user experience.

Team Leadership and Development: Leading and mentoring a team of four UI engineers, driving team productivity and efficiency. Implementing infrastructure improvements in continuous integration (CI) using GitHub Actions, and standardizing React component libraries, which have significantly enhanced team velocity and code quality.

Error and Performance Tracking: Integrating comprehensive error and performance tracking systems across all of StarTree’s web applications, ensuring robust and reliable performance. These integrations have helped identify and resolve issues promptly, contributing to a more stable and efficient user experience.

Architected and led development of LinkedIn’s internal data visualization platform for site speed analytics, empowering engineers across the company to monitor customer-facing page load performance.

• Built front-end applications using Ember.js to deliver intuitive, interactive dashboards.

• Led a cross-functional team of six backend and frontend engineers, mentoring junior developers to reach senior-level proficiency and promotion.

• Developed company-wide Node.js libraries that standardized internal web application infrastructure; over 100 internal Ember.js applications adopted these libraries for consistent UI and performance patterns.

Built an internal application to visualize site speed violations attributed to engineering page owners at scale, transforming how LinkedIn engineers monitor and interpret performance.

Spearheaded the migration from MapReduce batch jobs to real-time analytics pipelines using Spark and Pinot, reducing data availability SLA from 10 a.m. to 6 a.m.

Integrated Apache Pinot as the OLAP data store for LinkedIn's web performance data visualization applicaiton, powering queries over a terabyte of site performance data per day.

Extended internal web performance monitoring by integrating a Boomerang.js plugin to collect browser resource timings. Built a reusable waterfall visualization tool using Backbone.js, HTML, and CSS3.