Omi Sneha Singh
@omisnehasingh
Java backend developer specializing in Spring Boot microservices and scalable APIs.
What I'm looking for
I am a Java backend developer with hands-on experience building Spring Boot microservices, SAP CAP services, and REST APIs that improve performance and scalability. At SAP Labs I optimized services to reduce API response times, applied the Saga Pattern for distributed transactions, and increased unit test coverage, delivering reliable backend systems integrated with SAP HANA and MySQL.
I design and implement end-to-end backend features — from database queries and caching (Redis) to CI-ready containerized deployments — and have built invoicing and complaint-management systems, API automation tests with Karate, and analytics endpoints. I bring strong problem-solving skills demonstrated by competitive programming achievements and a research publication in machine learning.
Experience
Work history, roles, and key accomplishments
Developer
SAP Labs
Aug 2024 - Present (1 year 4 months)
Developed and optimized Java Spring Boot microservices for an internal Open Event SAP application, reducing API response time by 25% and improving scalability; implemented Ticket, Authentication, and Feedback services supporting 1K+ daily requests and applied the Saga pattern to reduce distributed data inconsistency.
Backend Developer
Independent Project
Dec 2024 - Mar 2025 (3 months)
Designed and developed a backend invoicing system (Dec 2024–Mar 2025) supporting 30+ active users and 200+ monthly invoices; implemented MySQL persistence, Redis caching to cut DB load 40%, AWS SES email delivery, and containerized services with Docker for deployment.
Education
Degrees, certifications, and relevant coursework
C.V. Raman Global University
Bachelor of Technology, Computer Science and Engineering
2020 - 2024
Grade: 9.04/10
Activities and societies: Research publication: Digital Diagnosis: A Machine Learning Perspective on Plant Disease Detection (IEEE Conference).
Completed a Bachelor of Technology in Computer Science and Engineering with a CGPA of 9.04/10 and published research on machine learning-based plant disease detection.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Job categories
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