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Gayathri Mattaparthi

About

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Haryana, India

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Résumé

Jobs verified_user 0% verified
  • Uber
    Full Stack Software Developer
    Uber
    Mar 2024 - Current (2 years 2 months)
    Deployed 2+ Express.js across 5 production applications, enabling real-time updates for 100+ driver availability checks and 50,000+ daily food order processes, ensuring seamless backend-frontend integration for a technology platform. Designed scalable backend systems using Java and Spring Boot, leveraging collaborative problem-solving to streamline architecture, improving system efficiency for high-traffic applications. Developed responsive frontend components with React.js and TypeScript, applying user-centric design principles to enhance mobile app responsiveness and accessibility. Implemented CI/CD pipelines via AWS CodePipeline and Docker, integrating systematic troubleshooting to accelerate deployment cycles and ensure seamless product
  • Accenture
    Software Developer
    Accenture
    Oct 2019 - Nov 2021 (2 years 2 months)
    Architected dynamic user interfaces with Angular and Bootstrap, deploying applications via Azure Static Web Apps to ensure scalability, which boosted client engagement. Engineered RESTful APIs using Spring Boot and Spring Data JPA, integrating MySQL databases to automate CRUD operations, reducing manual data entry errors. Built serverless micro services with Node.js and MongoDB, leveraging Azure Functions for event-driven workflows, which cut latency by 25% in high-traffic scenarios. Deployed enterprise-grade applications on Azure App Services using ASP.NET Core (C#) and Entity Framework Core, optimizing SQL Server queries to accelerate transaction processing by 1.2 seconds. Standardized data exchange protocols using XML (XSD validation) an
  • Airbnb
    Software Developer Intern
    Airbnb
    Oct 2018 - Sep 2019 (1 year)
    Designed and developed scalable backend services using ASP.NET Core and RESTful APIs, employing Entity Framework Core for database interactions, which reduced latency by 200 milliseconds and improved booking processing efficiency through a collaborative approach with product teams. Optimized performance of critical microservices by implementing caching mechanisms with Redis, resolving bottlenecks through problem-solving techniques, and enhancing user experience during peak traffic with 150-millisecond improvement in API response times. Spearheaded CI/CD pipeline enhancements using Azure DevOps, Kubernetes, and Docker, fostering teamwork to reduce average deployment time by two hours and accelerate feature delivery. Integrated backend system
Education verified_user 0% verified
  • W
    Master of Science in Data Science
    Western Michigan University
    Jan 2022 - Dec 2023 (2 years)
  • Jawaharlal Nehru Technological University
    Bachelor of Technology in Computer Science
    Jawaharlal Nehru Technological University
    Jun 2015 - May 2019 (4 years)
  • D
    Data Structures and Algorithms Specialization
    Coursera
  • C
    Certified Kubernetes Administrator (CKA)
    The Linux Foundation
  • P
    Python for Data Science and Machine Learning
    Udacity
  • G
    Google Professional Cloud Architect
    Google Cloud
  • M
    Microsoft Certified: Azure Solutions Architect Expert
Projects (professional or personal) verified_user 0% verified
  • A
    AI-Powered Recommendation Engine
    Generated React.js components for designing an interactive front-end interface displaying personalized recommendations, processing 50+ user queries daily with real-time updates to enhance user engagement and satisfaction. Integrated Spring-based backend logic for the AI-Powered Recommendation Engine, implementing scalable algorithms to process preferences & generate personalized suggestions, reducing recommendation latency and supporting 200+ concurrent users.
  • S
    Scalable E - Commerce Platform
    Developed Restful APIs using Spring for the Scalable E-Commerce Platform, designing a backend to handle 500+ transactions per minute, integrating secure payment gateways and inventory management systems, decreasing checkout latency by 0.6 seconds for an enhanced customer experience. Devised AWS infrastructure for utilizing EC2 and RDS to support concurrent users during peak sales, auto-scaling configurations to maintain uptime while minimizing operational costs by 15% through resource management.