Shovan (Sho)

Backend Developer

Bangalore, India 0+ yrs exp 87 · Excellent

About

Dedicated Backend Developer specializing in Node.js and TypeScript, with hands-on experience building scalable REST APIs, microservices, and asynchronous data pipelines. Possesses complementary expertise in Python for AI integrations and data extraction. Adept at optimizing database architectures, utilizing vector search for RAG implementations, and deploying containerized applications. Focused on backend reliability, low-latency API performance, and distributed system design.

Skills & Expertise (30)

Python Intermediate

5.5/10

Years Exp

Node.js Intermediate

5.5/10

Years Exp

Microservices Architecture Intermediate

5.5/10

Years Exp

JavaScript Intermediate

5.5/10

Years Exp

Microservices Intermediate

5.5/10

Years Exp

REST API design Intermediate

5.5/10

Years Exp

Typescript Intermediate

5.0/10

Years Exp

ETL Pipelines Intermediate

5.0/10

Years Exp

Event-driven workflows Intermediate

5.0/10

Years Exp

Postman Intermediate

5.0/10

Years Exp

GitHub Intermediate

5.0/10

Years Exp

Git Intermediate

5.0/10

Years Exp

Docker Intermediate

5.0/10

Years Exp

MongoDb Intermediate

5.0/10

Years Exp

Django Intermediate

5.0/10

Years Exp

Express.js Intermediate

5.0/10

Years Exp

Docker Compose Intermediate

4.5/10

Years Exp

Elasticsearch Intermediate

4.5/10

Years Exp

Redis Intermediate

4.5/10

Years Exp

FastAPI Intermediate

4.5/10

Years Exp

Socket.IO Intermediate

4.5/10

Years Exp

Cloudinary SQL Javascript (ES6+ Model Context Protocol Bun ETL RAG Pipelines Vector Embeddings Qdrant

Work Experience

Backend Developer Intern

Oggangs Pvt. Ltd.

Feb 2025 - Dec 2025

Built and optimized core REST APIs using Node.js and Express.js, managing secure user authentication and complex business logic to reliably serve over 50,000+ active monthly requests. Architected asynchronous background job pipelines utilizing Bull.js and Redis in a Node.js environment, offloading heavy data scraping workflows and reducing core API response latency by 42%. Formulated MongoDB indexing strategies for distributed, high-write database workloads and containerized backend services using Docker to guarantee uniform local and staging environments. Engineered an internal data enrichment microservice using Python (Django) for an ETL pipeline, extracting and cleaning raw text data with a 95% processing success rate. Configured Elasticsearch clusters for full-text search and faceted filtering, achieving sub-100ms retrieval speeds across datasets exceeding 2 million unstructured documents. Programmed internal AI-driven APIs to extract structured information from conversations using LLMs, auto-generating clean product records and cutting manual data entry overhead by 60%.