Optimize backend performance with query tuning, indexing, and load testing.
Maintain real-time data synchronization systems processing millions of records daily.
Implement asynchronous pipelines with Pub/Sub and Redis caching.
Improve system responsiveness and reduce synchronization latency.
Implement resilience patterns, reducing production incidents.
Manage zero-downtime schema migrations with backward-compatible deployments.
Contribute to migrating legacy systems to microservices.
Preferred Skills & Qualifications:
Bachelor’s degree in computer science or related field (Master’s preferred)
3–5 years of backend development experience (Java, Spring Boot)
Proficiency in Docker, Kubernetes, Kafka, MQTT, and cloud platforms (AWS/GCP)
Strong experience with SQL, relational database design, and optimization
Familiarity with API security (JWT, OAuth2, RBAC, OWASP) and scalable SaaS systems
Experience in CI/CD, performance tuning, and cloud-native deployments
Hands-on experience with Kubernetes and cloud-native environments
Proven ability in real-time data synchronization systems and performance optimization
Experience with zero-downtime schema migrations and resilient systems
Familiarity with AI/ML integrations (nice-to-have)
Cloud deployment experience on AWS and/or GCP
Proficient with Git, Bitbucket, and CI/CD workflows
Strong problem-solving, debugging, and analytical skills
Ability to work in a fast-paced, collaborative startup or enterprise environment
Knowledge of API security (JWT, OAuth2, RBAC, OWASP practices) and understanding of multi-tenant architectures and scalable SaaS systems
Experience working on HES, MDM real-time platforms, and distributed synchronization systems processing million records per day across multiple external systems
Proven experience in defining reliability standards such as idempotency, retry/backoff, and concurrency control, reducing recurring incidents
Experience owning zero-downtime schema migration strategy using Goose and backward-compatible deployments
Experience building real-time data synchronization systems, eliminating stale data cycles, and improving responsiveness
Proven ability to reduce synchronization latency across multiple external systems
Improved system reliability and reduced production incidents through implementation of resilience patterns
Designed asynchronous pipelines using Pub/Sub and Redis caching
Strong understanding of microservices, event-driven architecture, and high-scale REST APIs