Arpita Kumari

Software Engineer

Delhi, India2 yrs 4 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Designed scalable microservices handling 5K+ transactions daily.
Developed a decision engine saving over 5Cr annually.
Reduced production incidents from 40 to 4 per week.

Stackforce AI infers this person is a Backend-heavy SaaS Engineer with expertise in scalable systems.

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Skills

Core Skills

JavaMicroservices

Other Skills

Apache KafkaRedisDebuggingElasticsearchEngineeringJava DevelopmentMultithreadingGrafanaPrompt EngineeringPostman APIJiraJenkinsREST APIsMicrosoft ExcelMicrosoft Power BI

About

Software Engineer with 2+ years of experience building scalable backend systems using Java, Spring Boot, and event-driven microservices. Currently working at Moglix on high-volume order and inventory platforms that process thousands of transactions daily. I enjoy solving complex production issues, debugging distributed systems, and designing reliable backend architectures.

Experience

2 yrs 4 mos

Total Experience

2 yrs 3 mos

Average Tenure

1 mo

Current Experience

Airtel digital

Software Engineer - Deputy Manager

May 2026 – Present · 1 mo · Gurugram · Hybrid

JavaApache KafkaMicroservices

Moglix

Software Engineer

Feb 2024 – May 2026 · 2 yrs 3 mos · Noida · On-site

Designed and built scalable event-driven microservices for order and inventory systems, handling 5K+ daily transactions and reducing latency from hours to seconds
Designed and developed a rule-based decision engine for delivery breach detection, preventing incorrect penalty computation and saving 5Cr+ annually
Architected and implemented PaaS Supplier ARC automation, enabling configurable supplier assignment (CPN + Plant + optional Selling Price) and conditional SPO creation; saved ~350 man-hours/month
Ensured data consistency across distributed systems by implementing idempotent APIs and request deduplication, reducing inventory mismatches by 90%
Developed Kafka-based asynchronous processing pipelines with retry-safe mechanisms to ensure reliable high-throughput event handling
Optimized system performance using Redis caching and query tuning, improving API throughput by ~40%
Resolved critical production issues (DB locks, transactional inconsistencies), reducing incidents from 40 to 4 per week
Led root cause analysis of distributed failures, using logs, database state, and tracing to implement permanent fixes and improve system reliability