Mar 2023 – May 2024 · 1 yr 2 mos

• Architected and deployed a distributed observability and analysis platform integrating AWS CloudWatch, Protobuf, S3, and Fargate batch jobs to trace cluster and partition lifecycles across large-scale systems, reducing critical incident investigation time by 98% (from 4+ hours to <60 seconds) for 50+ production clusters.
• Engineered machine learning-powered anomaly detection pipeline using statistical models and rule-based classifiers to identify abnormal lifecycle patterns and potential security threats across distributed systems, reducing mean time to resolution (MTTR) by 95% for on-call engineers.
• Streamlined log data ingestion, aggregation, and visualization workflows using cloud-native services, eliminating manual log correlation and improving operational visibility across distributed services by 60%.
• Designed backend microservices and APIs supporting Power BI dashboards across sync, authentication, orchestration, alerting, and worker services, applying object-oriented design and common design patterns to deliver modular, maintainable services supporting scalable analytics and reporting workflows.
• Led end-to-end design and development of backend microservices supporting authentication, orchestration, alerting, and background workers; architected Kafka-based real-time streaming and batch processing pipelines processing 5M+ daily events (200+ events/sec) with 99.9% uptime, supporting real-time analytics for 10,000+ enterprise customers.
• Architected a distributed, multi-tenant data platform using MongoDB, PostgreSQL, and Redis with consistent hashing and rate limiting, reducing hot-partition p99 latency by 70% (600 ms to 180 ms) while sustaining linear scalability under peak production traffic.
• Managed cross-functional team of three engineers, reviewing code, guiding architectural decisions, and delivering secure REST and gRPC services with OAuth 2.0 and JWT authentication, reducing payment transaction errors by 40%.

Jan 2022 – Mar 2023 · 1 yr 2 mos

• Designed and operated Kafka-based event processing pipelines with partition-aware producers, consumer groups, and idempotent handlers, reducing duplicate message processing by 95% and ensuring reliable, fault-tolerant delivery.
• Engineered advanced caching and indexing layers using Redis, MongoDB, and Elasticsearch, optimizing query execution paths and reducing latency, improving execution speed and real-time user interactions by 60%.
• Built a fault-tolerant alerting and monitoring service using AWS Lambda, SQS, SNS, CloudWatch, and DynamoDB Streams, implementing retry-safe, idempotent workflows that reduced production downtime by 70%.
• Led the migration from AngularJS to React.js and TypeScript, refactoring legacy components into modular, testable codebases, reducing technical debt and accelerating QA feedback cycles through improved test coverage and linting.
• Participated in on-call rotation, driving continuous improvements in system availability, reliability, and incident response through proactive monitoring and automated remediation.

May 2020 – Jul 2021 · 1 yr 2 mos

• Engineered data ingestion and transformation pipelines integrated with AWS S3, improving data reliability by 30% and reducing manual intervention in reporting and analytics workflows.
• Developed and maintained unit and integration test suites for backend microservices and data pipelines using JUnit, Mockito, and TestNG, achieving 85%+ code coverage and improving regression detection rates.
• Implemented load balancing, auto-scaling, and health checks for microservices using Nginx, Kubernetes, and AWS ALB, ensuring high availability, seamless traffic distribution, and zero-downtime deployments under production load.