Ebad Rahman

Software development professional and IIT graduate with extensive experience in the Digital Payments Industry. Skilled in designing and implementing robust data pipelines and backend systems leveraging AWS. Currently working in Pine Labs, managing core services within the payment ecosystem. Gained significant experience in building high-performance scalable microservices, with proficiency in microservice architecture and distributed systems.

Software Developer - Blinkit - Gurugram, India

(2024-10)

• Key contributor to the Personalization Service, a Golang-based upstream system serving personalized feeds and product recommendations to the orchestration layer; powering multiple recommendation widgets across the app.
• Optimized high-traffic APIs by merging redundant calls, introducing parallel execution and slightly redesigning workflow including a critical API handling throughput of 27M rpm by cutting p99 latency from 800ms to 490ms
• Solved an existing org-wide problem by developing the Dispatcher Service using Kafka, featuring flexible, config-driven routing per team, eliminating repetitive, inefficient consumer setup across teams for receiving model-served data.
• Improved service observability using Grafana, StatsD, and Datadog for real-time monitoring, distributed tracing, and profiling alongside AWS console-based infra and database health checks, enabling faster debugging of production issues.
• Built an internal debugging dashboard, leveraging Claude Code, to inspect recommendations and perform ad-hoc updates; secured behind Kong Gateway to prevent unauthorized direct API access
• Proposed and developed widgets focusing on specific cohorts like fitness, driving a positive impact on business.

Software Developer - Pine Labs - Noida, India

(2024-07 - 2025-10)

• Decoupled the payment initiation component from a legacy .NET-based Payment Controller into a standalone, scalable Spring Boot microservice on AWS, supporting card and UPI payment modes; improved database interactions with connection pooling and Redis caching, cutting p95 latency from 400ms to 90ms
• Developed an event-driven architecture using MQTT for asynchronous payment initiation event, and leading reliability initiatives including stress testing to ensure robust performance under high-traffic scenarios.
• Designed a callback service exposed to acquirer banks to notify transaction status asynchronously, including handling delayed responses and timeouts in the payment flow.
• Owned end-to-end backend development of the Pine Labs Lounge Access Program across airports, integrating with card networks including Visa and RuPay to enable real-time, spend-based lounge eligibility decisions.

Data Science Intern - IITM Research Park - Chennai, India

(2023-06 - 2023-07)

• Conducted comprehensive time series analysis on 900,000+ records across 216 subsystems, enabling predictive modeling for long-term expenditure forecasting
• Created and trained Artificial Neural Network (ANN) models to forecast infrastructure-based spending trends, delivering actionable insights that improved budget allocation and optimized operational costs

B.Tech - Chemical Engineering - Indian Institute of Technology - Madras (2024-05)