Led optimization of ride allocation microservices using Java, Spring Boot, Kafka, and Redis on AWS, improving system assignment rate from 92% to 97%. Implemented multithreading techniques, reducing allocation runtime from ~4 minutes to ~1 minute. Rewrote the central location service in GoLang, reducing cold boot time from 45 minutes to 50 seconds by optimizing .pbf file handling and service boot flow. Separated the central Slots Service, leading to a 33% increase in ride bookings through improved slots management and system modularization. Developed a dynamic pricing microservice, improving booking efficiency by 20% and boosting revenue by 8%. Established real-time data pipelines connecting Engineering and Data Science teams, reducing ride delays by 30% and early arrivals by 16%. Integrated ELK stack-based monitoring and alerting pipelines, improving production incident response times by 70% and enhancing system uptime from 99.9% to 99.99%. Integrated traffic index with the location service in a side-car pattern, reducing Google ETA dependency by 20% and enhancing ETA accuracy using ODRD estimations.