Ganesh Rai
Software Engineer II • Backend & Distributed Systems
Talent
Greater NoidaMember since June 17, 2026
JavaSpring BootREST APIsMicroservicesDistributed SystemsEvent-Driven ArchitectureApache KafkaPostgreSQLKubernetesAzureTest AutomationDatadogPerformance Tuning
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JavaSpring BootREST APIsMicroservicesDistributed Systems
About
Backend Software Engineer with experience building scalable microservices and distributed systems in Java, Spring Boot and Kafka on GCP and Azure. Experienced in production incident management, event-driven architectures, JVM performance tuning and backend platform development for enterprise-scale applications.
Experience
Software Engineer II at Ultimate Kronos Group (UKG) (2025-04 – Present)
- Migrated a CPU-intensive scheduling workflow to an event-driven architecture using Apache Kafka on GCP, reducing peak-hour response times by 35% across 10,000+ daily enterprise scheduling requests.
- Led incident response for recurring Kubernetes OOM pod crashes across a Java 17 migration, isolating native memory leaks and JVM heap misconfiguration via heap-dump and GC-log analysis, and restoring production stability within 48 hours while unblocking 5 dependent teams.
- Slashed p95 API latency by 25% and boosted throughput by 40% via JVM thread-contention profiling, Spring Boot hot-path re-engineering, and blocking I/O elimination — confirmed through Datadog APM monitoring across 3 high-traffic endpoints.
- Deployed Caffeine in-memory caching for high-frequency shift-query APIs, cutting database round-trips by 60% and holding p99 latency-critical response times below 200 ms during peak-load spikes.
- Coached 2 junior engineers on JVM diagnostics, JUnit-based test automation, and Datadog observability, shrinking mean on-call incident resolution time by 25% through structured mentorship.
Software Engineer at Jio Platforms Limited (2022-07 – 2025-03)
- Built REST APIs on Azure using Spring Boot and PostgreSQL for a clinical annotation platform serving 50+ concurrent clinicians, adding versioning and consensus workflows that lifted ML dataset quality by 20%.
- Delivered a Data Dictionary service on Azure to catalogue ownership, lineage, and quality metrics across 200+ data assets, raising data accuracy by 30% and trimming cross-team approval cycles by 40%.
- Extended the Service Quality Monitoring platform with remote WiFi router diagnostics spanning 1M+ deployed devices, enabling proactive fault detection that dropped field-engineer dispatches by 25% and repair costs by 20%.
Education
B.Tech in Electrical & Electronics Engineering – Ramaiah Institute of Technology (2018 – 2022)
Skills
Software Engineer IIBackend & Distributed Systems
