Mishal Shah Email and Phone Number

Tech stack: Python, Django, MySQL, Redis, Nginx, Kubernetes, Docker, React

Tech stack: Golang, Docker, Python, Typescript, AWS• Reduced human intervention to extract pricing data from investor rate sheets under 30 seconds by developing a generalised parser in Golang.• Spearheaded the development for Golang parser engine and infrastructure in AWS using AWS Lambda, AWS Cloudwatch, AWS Athena, AWS EFS and AWS RDS.• Improved responsiveness for the loan affordability algorithm in the eligibility engine by 10% using Pareto efficiency techniques.

Domain: Full-stack and infrastructure engineeringTech stack: Python, Node.js, AWS• Reduced page load times for React application by 60% using lazy loading and gstreamer optimizations to handle different runtime resolutions for live 4k rtsp video streams dynamically.• Scaled Mobile App Analytics Engine to process 100 events/second using Node.js microservices containerized via AWS ECS.• Leveraged health check module in ASU mobile app using AWS SQS, Lambda, API Gateways, Bluetooth mesh and push notifications to prevent ∼200 potential Covid-19 cases on campus.• Spearheading the rapid prototyping of AWS resources in production using Terraform and Jenkins reducing deployment lifecycle timeframe from 6 minutes to 30 seconds on average.

Domain: Distributed systems and Big dataTech stack: Python, Elasticsearch• Reduced search latency by 5ms on average for ∼300 gigabytes of payments’ data in Elasticsearch over legacy Solr cluster using JVM heap optimisations and optimal sharding layout.•Improved resiliency for Elastic and Kafka cluster data nodes in production using the service discovery mechanism with HashiCorp Consul increasing the uptime from 85% to 99%.• Reduced Elastic cluster configuration and setup time from 1 day to 2 hours using multi-threading performance testing framework in Python to extrapolate high performance benchmark configurations.

Domain: Distributed systems and DevopsTech stack: Java 8, MongoDB, Elasticsearch stack, gRPC, BASH scripting• Reduced reconciliation time from 3 hours to 10 seconds for financial trade data in on-premise MongoDB with upstream trade systems using polyglot microservices architecture and BASH scripts over legacy Java code.• Optimised API results’ size by removing redundancy using cursor-based pagination.• Slashed turnaround time for finding missing trades’ information by ∼40% using Elasticsearch stack in production alongwith DropWizard framework to capture anamolies in trade flow.

Domain: Mobile App developmentTech stack: React-native, Objective-C, Android and AWS* As part of the core development team, I incorporated cursor-based pagination and dispatch threads to the newsfeed API to reduce newsfeed load time from over 5 seconds to 1.4 seconds leading to 20% boost in the end-user engagement.* Redesigned the user interface on the iOS platform resulting in 25% increase in user retention. * Ported sections of iOS modules to react-native platform to ensure consistency and leverage iOS native support functions.