Building a revolutionary real-time streaming denormalization engine in Kafka

Maintain flagship API that serves ~2 billion API calls a month for 5000 clients (Walmart, Target etc.)

Provide feedback to Confluent on their toolkit around Kafka (KSQL, Schema Registry, Rest Proxy)

Rebuilt API platform for Target and Sears. 10x reduction in response latency (~1s -> ~100ms). Saved the company thousands in AWS hosting costs. Migration to new platform was done seamlessly with no downtime.

Kafka, Elasticsearch

Scala, Java, Ruby

AWS, Jenkins, Kubernetes

Consolidated JIRA, Jenkins, GitHub data into unified, real-time dashboard. Backed by an Elasticsearch cluster and a Kibana front-end.

Parallelized Selenium test suite bringing down test times considerably

Developed a new responsive face for the company web app in React using Facebook’s Flux pattern. Utilized by thousands of clinicians and doctors across the world everyday.

Added freehand annotation tool to viewer. Optimized with the Douglas–Peucker algorithm.

Improved efficiency for clients by implementing error-specific pages on server side leading to a reduction in customer service calls

Contributed to release of BES 12 implemented on Blackberry, Android and iOS