Senior Java Software Engineer

We are hiring an experienced Senior Software Engineer to design, build and maintain high-performance, secure Java back-end systems for a large-scale digital services platform. You will work end-to-end – from solution design through implementation, testing and production support – collaborating with product managers and cross-functional teams to deliver reliable, scalable services and well-designed APIs.

• Design and develop high-performance, scalable back-end systems and effective APIs.
• Build and maintain well-functioning databases and applications.
• Implement security and data-protection controls across services.
• Write clean, maintainable, well-tested code; debug and resolve production issues.
• Produce clear technical documentation and participate in code reviews.
• Communicate with stakeholders and service providers to align technical requirements.
• Stay current with tools and practices to continuously improve the back-end platform.

• Bachelor’s or Master’s degree in Computer Science or a related field.
• 5+ years’ hands-on software engineering experience at a senior level.
• Strong CS fundamentals: algorithms, data structures, OOP, design patterns, software architecture, database design and UML.

• Java (11+) and Spring Boot – current, hands-on, build-level experience (not architecture/oversight only).
• Oracle Database – SQL and PL/SQL, indexing, query tuning and reading execution plans.
• REST and SOAP web services – designing and consuming both.
• API security – JWT (access vs refresh tokens), Spring Security, and OAuth2 / OIDC.
• Oracle Web Logic and Apache Tomcat – deployment, tuning and troubleshooting on application servers.

• Apache Kafka or RabbitMQ and event-driven architecture.
• Transactional outbox pattern for save-and-publish consistency.
• Idempotent consumers and duplicate-message handling (unique key + de-duplication).
• Resilience patterns – circuit breaker, retry with back-off, fallback, bulkhead and rate limiting (e.g. Resilience4j).
• Distributed locking for scheduled jobs across multiple instances/pods (e.g. Shed Lock, Redis or leader election).
• SOA and microservices architecture; awareness of CQRS.

• Diagnosing latency when CPU is low (thread- and connection-pool exhaustion, GC, blocking I/O).
• Query optimisation, avoiding full table scans, and resolving the N+1 problem (fetch join, entity graph, batching).
• Optimistic vs pessimistic locking and handling race conditions.
• Memory-leak diagnosis using heap dumps and profilers