Join NTT DATA, a global leader in business and technology services, and contribute to innovative client solutions. We are seeking a seasoned Java Full Stack Developer with 4-6 years of experience to enhance our team in Bangalore. This role focuses on developing scalable enterprise applications and microservices, leveraging both frontend and backend expertise.

As a forward-thinking organization, NTT DATA encourages adaptability and a passion for growth. We are looking for individuals who are eager to learn and embrace new technologies, contributing to our mission of accelerating client success and making a positive societal impact.

Develop robust and scalable full-stack applications and EPDM services. Craft engaging user interfaces using React and Eclipse/Engineering Client. Build and refine server-side components with Java, JEE, EJB, and Spring Boot microservices. Ensure seamless data integration with IBM DB2 and PostgreSQL databases. Actively participate in code reviews, debugging, and performance optimization. Utilize Docker and basic DevOps tools for efficient deployment. Design and consume RESTful services and KAFKA for sophisticated integration use cases. Collaborate effectively within Agile teams, participating in PI planning and other ceremonies.

A minimum of 4–6 years of hands-on experience as a Java Full Stack Developer is essential. Demonstrable expertise in Java, JEE (EJB), and Spring Boot is required. Proficiency in developing frontend applications with React JS and Eclipse RCP / rich client applications is crucial. A strong grasp of 3-tier architecture and client-server systems is expected. Experience with relational databases such as IBM DB2 or PostgreSQL is necessary. Familiarity with ORM frameworks, ideally OpenJPA/Hibernate, is important. Practical experience in REST API design, KAFKA, and integration technologies is key. Hands-on experience with Docker and DevOps tools is a must. Proficiency in Git version control and familiarity with JIRA & Confluence are required. A good understanding of AI/ML concepts, including LLMs, model APIs, embeddings, and automation use-cases, is beneficial.