Hi 👋, This is Jagonmoy Dey
- 📫 Reach me at : jagonmoydey1997@gmail.com
- Connect with me :
I'm passionate about leveraging technology to solve real-world problems. As a Full Stack Software Engineer, I specialize in front-end development with Next.js and back-end development with Nest.js. My expertise includes tackling complex challenges with data structures and algorithms, along with experience in Natural Language Processing. Currently, I'm working on a multi-tenant SaaS product which is a subscription management system.
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Frontend Development
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Optimized images using Next/Image and imgix, implemented server-side fetching, server actions, and Next.js cache revalidation. Achieved a 100% SEO score and 100% best practices score in a Google Lighthouse report, improving overall page load performance from 55% to 85%.
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Implemented custom fields integration for a multi-tenant front-end, built responsive UIs according to Figma, and developed well-maintained, reusable React.Js components.
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Utilized MJML to create responsive email templates, accommodating dynamic values for enhanced flexibility and personalization.
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Backend Development
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Worked with Nest.Js event queue architecture to facilitate automated email functions for both scheduled and event-driven tasks, serving over 200,000 users in Scandinavian countries.
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Optimized backend API performance and fine-tuned TypeORM SQL queries, resulting in a 1.5x improvement in API response times and overall system efficiency.
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Authentication
- Integrated external tenant application with the subscription system's OIDC using NextAuth.
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Testing
- Employed Playwright for end-to-end testing and Jest for unit testing to ensure the application's robustness and reliability.
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Data Structures and Algorithms
- Solved 1200+ data structure and algorithms problems, achieving a Codeforces rating of 1500+.
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Machine Learning
- Developed a speaker diarization system in undergrad thesis titled Speaker Diarization with Speech Recognition in Bengali using Bi-LSTM and integrated Google Cloud Speech-to-Text API for Bangla recognition, incorporating Voice Activity Detection, speaker segmentation, and clustering (k-means, Mean Shift).
