Parth Janakbhai Patel

About Me

Software Engineer based in Tucson, AZ with expertise in Backend & Cloud technologies. Passionate about building scalable microservices and optimizing complex systems.


Experience

Komatsu

Software Engineer | Tucson, AZ | February 2023 – Present

  • Safeguarded mission-critical mining operations valued at $100k+/hour by engineering a low-latency Kotlin microservice that synchronizes 500+ autonomous trucks, simultaneously cutting external integration time by 50%.
  • Achieved sub-second UI latency (previously multi-second) for the Fleet Management System by decoupling the C# adapter from the monolithic core, architecting a non-blocking asynchronous communication pattern for high-volume telemetry.
  • Slashed developer onboarding time by 75% (1 month to 1 week) by resurrecting a dormant API project, reverse-engineering legacy code, and establishing a robust Azure CI/CD pipeline that unblocked cross-team feature delivery.
  • Accelerated deployment velocity by 60% by architecting a zero-error Docker-based release pipeline with Bash automation, eliminating manual configuration drift for non-technical users.
  • Optimized geospatial rendering speed by 20% by integrating GeoServer with PostGIS and restructuring Hibernate/JPA queries to efficiently serve complex map object layers.
  • Centralized API security for 100+ daily internal requests by implementing an OAuth2/Keycloak gateway, reducing configuration overhead by 35% while enforcing strict access control policies.

Evernote

Software Engineer Intern | Remote, NY | June 2022 – August 2022

  • Shipped the "Repeat After Completion" feature to 50,000+ beta users by architecting complex temporal state management logic in TypeScript/GraphQL to handle dynamic recurring intervals across timezones.
  • Deployed a reusable task-filtering component to 200M+ users across Web, Mobile, and Desktop clients, strictly adhering to Figma design specs to ensure uniform UX at global scale.
  • Enhanced iOS touch responsiveness for millions of users by refactoring the date-picker state management logic, resolving main-thread blocking issues during high-frequency interactions.

ISRO – Space Applications Center

Research Intern | Ahmedabad, India | December 2020 – April 2021

  • Achieved 92% detection accuracy for oceanic eddies by engineering a Python deep learning pipeline (Mask R-CNN, YOLO), utilizing batch processing to analyze terabytes of satellite imagery without memory overflow.
  • Converted vague research requirements into precise ML specifications by transforming NetCDF data into Matplotlib visualizations, enabling the model to successfully classify cyclic vs. acyclic water patterns.

Skills

Languages

Kotlin, Java, Python, C#, TypeScript, C++, SQL, Bash

Backend & Cloud

Spring Boot, Node.js, Microservices, RESTful APIs, Docker, Kubernetes, Azure, GCP

DevOps & Tools

CI/CD Pipelines (GitHub Actions, Azure DevOps), Git, Maven, Gradle, Nginx

Data & Security

PostgreSQL, PostGIS, GeoServer, OAuth2, Keycloak, JWT, SAML2, Spring Security


Education

Stony Brook University

Stony Brook, NY | Master of Science in Computer Engineering | December 2022

Certifications: CodePath Professional Android Development (2022)