• Reduced latency of real-time application from 2 minutes to 500 milliseconds with 10K events/second for a customer base of 60,000 by re-designing and implementing a highly scalable distributed application.
• Saved ~80% ($200,000/year) on cost by fine tuning existing distributed applications in the cloud.
• Enabled customers to access their millions of call records through RESTful apis by building spring boot based microservices.
• Improved scalability and reduced maintenance of a customer facing legacy application by building python based serverless cloud applications in aws.
• Resolved business-critical hard problems with 3x performance improvement by fixing hotspotting , handling late event issues and migrating redis to cluster.
• Enabled customers to get summary metrics by implementing a 5 minute event aggregation application using spark .
• Defined coding standards for new products and coordinated with a team of 10 software developers onsite and offshore.
• Mentored and provided guidance for 3 summer interns to automate 25% of jira triaging created from customer feedback by doing stemming and labelling using NLP and classification using Machine Learning.
• Produced scalability metrics for elasticsearch and kafka for new products by doing data modeling and benchmarking elasticsearch indices ,dsl queries, kafka partitioning.
• Boosted search performance by 30% by fine tuning elastic search query dsl and implemented auto-complete and multi-field search on TeraBytes of data corpse.
