Results-driven Computer Science graduate with a strong foundation in Python, FastAPI, and robust database management (PostgreSQL, MongoDB). Proven ability to design, develop, and deploy scalable RESTful APIs and personalized recommendation systems. Ready to leverage strong problem-solving skills and a commitment to continuous learning to contribute to impactful backend development projects and deliver efficient, high-performance solutions.
SIWES Intern - Supply Chain Operations
Summary
Gained practical experience in supply chain operations, focusing on data processing, materials management, and logistics.
Highlights
Processed and managed supply chain data, including materials specification, procurement, and logistics, enhancing operational efficiency.
Generated comprehensive reports using Excel, providing insights into telecommunication materials and supply chain performance.
Developed a foundational understanding of end-to-end supply chain processes and data flow within a corporate environment.
Bachelor of Technology (B.Tech)
Computer Science
Diploma
Backend Engineering
Git (6), Docker (6), Pydantic (7), Redis (2), ThunderClient (6).
PostgreSQL (7), MongoDB (7).
RESTful API Development (8), JWT Authentication (8), Data Validation (7), Unit Testing (7), Logging (7).
Python (7), SQL (7), HTML (5), CSS (5), JavaScript (2).
FastAPI (7), Node.js (6), Express.js (6).
Summary
Developed a full music booking system enabling artists to manage availability and organizers to book artists. Implemented JWT authentication, rate limiting, booking approval/rejection, and PostgreSQL integration. Provided comprehensive OpenAPI documentation for easy testing and scalability.
Summary
Developed a fully functional movie listing API using Python and FastAPI, integrating features such as movie ratings, comments, and JWT-secured endpoints. Implemented PostgreSQL for data management, with unit testing and logging for efficient performance. Deployed on a cloud server with comprehensive API documentation.
Summary
Developed a personalized movie recommendation system using FastAPI and datasets to suggest movies based on user inputs (genres, titles). Implemented without user sign-ins, ensuring a seamless user experience. Designed the interface using Jinja templates, eliminating the need for front-end engineers. Project inspired by a study of AI and natural language processing to address decision fatigue in movie selection.
Summary
Created an API to facilitate appointment bookings between patients and doctors. Ensured that each doctor can only have one appointment with a patient at any time, handling conflicts and responding with appropriate status codes. Currently expanding the project by adding authentication, and integrating MongoDB and PostgreSQL for a more scalable solution.