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Arunkumar Gangula
Senior Full-Stack Software Engineer specializing in distributed systems and cloud microservices
Tempe, ArizonaGraduate Student Associate (GSA)11 years experienceSeniorTechnologyE-commerceRetail
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About
Product-minded full-stack engineer from CouponDunia who owned end-to-end notification and recommendation services at million-user scale. Built internal admin/analytics and operations dashboards in React/TypeScript with typed contracts and scalable Node.js REST APIs, and has deep microservices experience with Kafka/RabbitMQ (idempotency, retries/DLQs, partitioning, consumer tuning, and observability).
Experience
Graduate Student Associate (GSA)Arizona State University
Lead EngineerTimesGroup (CouponDunia)
Senior Software EngineerTimesGroup (CouponDunia)
Senior Software EngineerGood Glamm Group (BabyChakra)
Software EngineerDirecti
InternCognizant
Software EngineerArizona State University
Lead EngineerTimes Internet (CouponDunia)
Senior Software EngineerTimes Internet (CouponDunia)
Education
Arizona State Universitymaster, Software Engineering (2026)
Mumbai Universitybachelor, Information Technology (2014)
Key Strengths
- Owned end-to-end delivery of notification and recommendation services used by millions of users
- Rapid iteration using metrics-driven experimentation (CTR/conversion), feature flags, A/B tests, and incremental rollouts
- Strong reliability practices: CI/CD, monitoring, and fast rollback when metrics dip
- Designed scalable, strongly-typed React/TypeScript + Node.js systems with domain-based modular architecture
- Handled scale challenges in event-driven microservices (Kafka/RabbitMQ) with idempotency, retries, DLQs, and observability
- Performance optimization across stack (API response shaping, caching, React memoization/lazy loading)
- Built and drove adoption of internal tools for non-engineering teams via shadowing, weekly feedback loops, and clear time-savings
- Owned end-to-end production feature (frontend, backend, AWS deployment/ops) for high-scale notifications/engagement
- Performance tuning under peak traffic: DB contention fixes (profiling, indexing, join optimization, reduced writes)
- Scalability via async processing with Kafka consumers, Redis caching, and batching
- Operational excellence on AWS: monitoring, alarms, tracing, and autoscaling for traffic spikes
- Zero-downtime migration strategy (backward-compatible changes, dual writes/reads, rolling deploys, batched backfills)
- Reliable integrations/pipelines: idempotency, retries with exponential backoff, reconciliation/backfills, alerting
- High-ambiguity startup execution: shipped MVP payment integration with evolving requirements and iterated post-launch
- Maintainability improvements in microservices: standardized API contracts, shared modules, cleaner layering; reduced bugs and improved onboarding
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