Hi, I'm Atharv Pandey
I build systems that scale.
CS Undergrad at IIIT Bhopal (9.37 CGPA). I am a Full-Stack Engineer with a heavy emphasis on backend architecture. I thrive on architecting scalable microservices, designing robust databases, and building seamless, high-performance web applications from end to end.
Prod Tickets Resolved
Core Microservices Scaled
API Latency Achieved
Test Coverage Reached
Engineering DNA
Distributed Data Systems
Expertise in designing fault-tolerant systems using Kafka for event-driven architectures. Deep understanding of MongoDB & PostgreSQL modeling, indexing, and handling heavy read/write throughput via GraphQL and REST.
High-Performance APIs
Obsessed with latency reduction. Proficient in executing load tests via JMeter to identify bottlenecks, slashing response times from seconds to sub-500ms using caching, optimized DB queries, and payload minimization.
Enterprise Architecture
Bridging rapid prototyping with enterprise scale. Integrating Grafana, Datadog, & BigQuery for observability. Managing robust CI/CD, unit testing strategies, and strict JWT/RBAC security modules across Node.js and Spring Boot.
Work Experience
Software Engineering Intern
Payoneer (Skuad)
May 2025 - Feb 2026
Gurugram, Haryana
System Architecture
- Architected an end-to-end Resignation Flow via 5 GraphQL mutations, handling DB migrations (JSONB) and PDF/email triggers.
- Engineered robust role-based access checks (IsCEM/IsCSM) and resolved complex search filtering across Contractor and Vendor APIs.
Infrastructure & Data
- Established a centralized Kafka monitoring framework across 4 services, unifying consumers and implementing health checks.
- Executed Node.js v22 & Mongoose upgrades, fixed BigQuery sync pipelines, and set up Grafana cron dashboards.
- Built internal CLI tools in Go for automating deployment workflows and service health checks across microservices.
Performance Optimization
- Slashed API response times from seconds to ~250-600ms across 8+ heavy workflows by eliminating database bottlenecks and optimizing queries.
- Resolved slow Kafka message consumption by adding targeted MongoDB indexing, and conducted JMeter load testing to benchmark workflow stability.
Production Engineering
- Resolved 90+ Jira tickets and scaled unit test coverage from ~17% to 30%+ across 5 core services.
- Troubleshot 20+ critical prod bugs including currency conversion failures, missing flat-object mappings, and dropped invoice events.
How I Engineer
1Fault Tolerance First
I never assume the happy path. Before writing business logic, I establish centralized error frameworks and dead-letter queues. I ensure message processing reliability in event-driven systems by unifying Kafka consumers and writing strict validation schemas to prevent poisoned payloads from cascading.
2Data Modeling & Latency
Performance is an architecture problem, not an afterthought. I obsess over query plans, JSONB structuring, and strategic MongoDB/PostgreSQL indexing to slash read times. By running heavy JMeter load tests against GraphQL mutations, I actively eliminate database bottlenecks before they hit production.
3Zero-Downtime Execution
Shipping code is only half the job. I take ownership of the deployment lifecycle by configuring Grafana dashboards, executing major Node.js runtime upgrades, and rotating CI/CD pipeline tokens with zero impact to active users or data integrity pipelines (BigQuery).
Featured Work
A production-grade, full-stack document intelligence platform. Engineered a highly scalable Retrieval-Augmented Generation (RAG) pipeline utilizing Apache Tika for document parsing and pgvector to store 3072-dimensional embeddings for rapid cosine similarity search.
Vector Search Architecture
Integrated pgvector for high-performance vector operations and semantic search capabilities.
24 REST APIs
Exposed secure, JWT-authenticated endpoints seamlessly integrated into a containerized microservice architecture.
NestJS • GraphQL • TypeORM • PostgreSQL
Full-stack CMS with RBAC via JWT. Authored optimized GraphQL APIs for CRUD operations across 5 data models, integrating Supabase Storage for seamless media handling.
More Engineering Feats
FileShortcutter
Next-Gen EngineeringBuilt at extreme speed using AI coding tools (Claude Code, Cursor) and modern tooling for maximum engineering velocity. Despite the rapid prototyping pace, it features a comprehensive PRD, scalable design patterns, and robust architecture, proving that AI-augmented development doesn't mean compromising on clean code.
predictive-analytics-dashboard
Designed a real-time ETL pipeline and XGBoost predictive ML model for user conversion forecasting.
Loan Management System
A robust financial backend handling complex loan lifecycle processing, demonstrating secure transactional data structures and strict validation.
Ecommerce-SWE
Scalable E-commerce architecture showcasing high-throughput transactional processing.
Realtime_Object_Detection
Computer Vision project leveraging ML models for sub-second object classification.
Course-Edu
An educational platform tailored for streamlined course management.
Education
Indian Institute of Information Technology
B.Tech in Computer Science
Nov 2022 - Jun 2026 • Bhopal, MP
Active member of the Training & Placement (TnP) Cell and Teaching Assistant (DSA). Led management and outreach initiatives across the institute.
Research & Hackathons
NeuroVoice: Leveraging Neural Networks for Precise Gender Classification in Audio
Authored and published research on applied neural networks for complex audio processing.
- ▹ Qualified for Smart India Hackathon (SIH) Round 1.
- ▹ Qualified for Flipkart GRiD Round 1.