James Fabian Portfolio

Technical Skills

Front End Development: JavaScript (ES6+), JSX, TypeScript, TSX, HTML5, CSS3
Frameworks and Libraries: React, React Router, TanStack Query, Axios, Ant Design, Material UI, Tailwind CSS
Programming Languages: Java, Python
Databases: PostgreSQL, MySQL, MongoDB, Supabase, Firebase
Version Control: Git, GitHub, Bitbucket

Professional Experience

MAXBYTE TECHNOLOGIES

Role: Associate Software Engineer | 2023 – Present

Implemented a robust token-based authentication system, improving session security and user experience while reducing login interruptions by 40%.
Optimized byteFactory's user interface and backend integration, enhancing responsiveness, modularity, and performance, reducing bundle size by 20% and accelerating data-loading times with dynamic interactive graphs.
Collaborated with backend teams and clients to streamline REST API integrations, customize features, and resolve issues, achieving a 25% improvement in development efficiency and seamless frontend-backend integration.

EAPHARMICS

Role: Front End Lead | October 2024 – March 2025

Spearheaded the migration of the pharmaceutical application’s UI from Adobe Flex to ReactJS, achieving a 60% improvement in performance and responsiveness while aligning with international regulatory guidelines.
Optimized data fetching processes using TanStack Query, resulting in a 40% reduction in loading times and enhancing the user experience across complex workflows.
Implemented React Router for seamless navigation and Material UI for a modernized design, increasing user satisfaction and usability metrics by 80%.

Projects

Spotify Clone

Technologies: Next.js, TypeScript, Stripe, Supabase, Tailwind CSS

A responsive music streaming application with song upload functionality, advanced audio player components, and seamless real-time data handling using server-side React components. Integrated Stripe for secure payment processing and utilized Supabase for authentication, GitHub login, and media storage management.

AI Based Resume Parser

Technologies: Python, Flask, spaCy, pdfplumber, SQLite

This project allows you to extract personal details, education, work experience, and skills from a PDF resume using AI and NLP techniques. The application is built with Python and Flask and leverages several libraries including pdfplumber and spaCy for advanced text extraction and processing.

James Fabian