Open to opportunities

Sujal Dongol

@sujaldongol1

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Passionate backend developer building government-grade, scalable web systems.

Nepal

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What I'm looking for

I seek backend or full-stack roles at mission-driven teams building scalable, secure public-facing platforms where I can lead architecture, mentor developers, and deliver measurable impact.

I am a passionate software developer specializing in backend systems and large-scale digital governance platforms, with hands-on experience delivering government-grade applications and enterprise SaaS solutions that serve hundreds of thousands of citizens.

I have led architecture and implementation for multi-tenant, secure platforms using Laravel and the MERN stack, optimized performance with Redis and query tuning, and built RESTful APIs with JWT and Swagger. My projects include SmartPalika (100+ municipalities, 850,000+ citizens) and national digital transformation initiatives that improved transparency and operational efficiency.

I mentor junior developers, champion testing and code-review standards, and combine data engineering and ML experience to deliver reliable, data-driven solutions. I seek to continuously learn and contribute to impactful, citizen-centric technology projects.

Experience

Work history, roles, and key accomplishments

Current

Mid-Level Backend Developer

Current

Cellapp

Sep 2023 - Present (2 years)

Lead backend developer for SmartPalika platform serving 100+ municipalities and 850,000+ citizens; architected event-driven Laravel systems, built secure RESTful APIs, and improved response times by 40% via Redis caching and query optimization.

Laravel PHP MySQL MongoDB Redis RESTful APIs JWT Docker PHPUnit

Backend Developer (Project)

ReKnovi

Designed and implemented MeetPoint meeting-scheduling application with Express.js backend, real-time communication (Agora, Firebase), multi-gateway payments, and scalable file storage using Multer-S3 and Docker.

JWT Firebase Agora Stripe Docker Multer S3 OAUTH2

Machine Learning Developer

Prime College

Developed MEDIX disease diagnosis system as final-year project using Logistic Regression and XGBoost on 100k+ records, achieving up to 97% accuracy for diabetes prediction and delivering production-ready prediction APIs and UI.

Python Pandas NumPy scikit learn XGBoost Jupyter RESTful APIs data preprocessing

Education

Degrees, certifications, and relevant coursework

Prime College

Bachelor of Science, Computer Science and Information Technology

2019 - 2024

Completed a Bachelor of Science in Computer Science and Information Technology focused on software development, data engineering, and machine-learning applications.