Backend Java Developer

Position Overview The Applications Development Intermediate Programmer Analyst (C11) will participate in the design, development, and modernization of high-performance enterprise applications. This role requires a strong engineering background with 4–9 years of software development experience, specializing in modern Java (hands-on with recent Java versions like 17/21), Microservices Architecture, Docker containerization, Python scripting/development, and extensive Oracle PL/SQL programming. The ideal candidate possesses an appetite for tackling complex architectural and business challenges, demonstrates proactive collaboration and communication across distributed teams, and actively leverages Generative AI tools and automation practices to optimize output, accelerate development cycles, and ensure engineering excellence. Role Summary Job Title: Applications Development Intmd Programmer Analyst Grade / Level: C11 Domain: Global Technology / Applications Development Core Technology Stack: Java 17/21+, Spring Boot, Microservices Architecture, Docker / Container Images, Python, Oracle Database & PL/SQL, REST APIs, CI/CD, GenAI Dev & Automation Tools Key Responsibilities 1. Application Design, Microservices & Core Engineering Architect, build, and deploy resilient, scalable Microservices and distributed backend components using modern Java (Java 17/21+) and the Spring framework ecosystem (Spring Boot, Spring Cloud). Build, optimize, and manage Docker container images, container runtimes, and local/orchestrated build pipelines. Develop and maintain automation scripts, utilities, or data processing components using Python. Perform comprehensive unit and integration testing (JUnit 5, Mockito, Testcontainers) and maintain rigorous code quality and security standards. 2. Database Engineering & PL/SQL Programming Design, optimize, and maintain complex relational database structures in Oracle. Write, refactor, and fine-tune complex PL/SQL packages, stored procedures, functions, triggers, and views. Perform SQL query optimization, execution plan analysis, index strategy implementation, and database performance tuning for high-throughput, low-latency transaction processing. 3. AI-Driven Productivity, Automation & Optimization Actively utilize Generative AI tooling (e.g., coding assistants, automated test generators, prompt engineering, AI refactoring tools) to maximize engineering velocity and optimize application code and processes. Implement automated test pipelines, code generation utilities, and build-automation scripts across Python/Java toolchains to eliminate manual engineering overhead. Champion automation-first approaches in local development loops, deployment pipelines, and operational monitoring. 4. Agile Delivery, Problem Solving & Teamwork Collaborate actively within an Agile/Scrum team structure with Product Owners, Architects, Business Analysts, and Quality Engineers.