Java Spring Boot Developer

Job Title: Java Spring boot Developer

Location:

Job Type: Full-Time

Experience: 6 + Years

Job Summary :

• Key Responsibility :

• Design, develop, and deploy

  Java Spring Boot

   applications on

  Red Hat OpenShift

  .
• Build robust data pipelines with

  Apache Kafka

   for high-throughput ingestion and real-time processing.
• Implement transformation and routing logic using

  Apache Camel

   and

  Enterprise Integration Patterns (EIPs)

  .
• Develop components that interface with various protocols including

  HTTP

  ,

  JMS

  , and database systems (SQL/NoSQL).
• Utilize

  Apache Flink

   or similar tools for complex event and stream processing where necessary.
• Integrate observability solutions (e.g., Prometheus, Grafana, ELK, OpenTelemetry) to ensure monitoring, logging, and alerting.
• Collaborate with AI/ML teams to integrate or enable AI-driven capabilities within applications.
• Write unit and integration tests, participate in code reviews, and support CI/CD practices.
• Troubleshoot and optimize application performance and data flows in production environments

Required Skills & Qualification

• 5+ years

   of hands-on experience in Java development with strong proficiency in

  Spring Boot

  .
• Solid experience with

  Apache Kafka

   (consumer/producer patterns, schema registry, Kafka Streams is a plus).
• Proficient in

  Apache Camel

   and understanding of

  EIPs

   (routing, transformation, aggregation, etc.).
• Strong grasp of various

  protocols

   (HTTP, JMS, TCP) and

  messaging paradigms

  .
• In-depth understanding of

  database concepts

    both relational and NoSQL.
• Experience with

  stream processing technologies

   such as

  Apache Flink

  , Kafka Streams, or Spark Streaming.
• Familiarity with

  OpenShift

   or similar container platforms (Kubernetes, Docker).
• Knowledge of

  observability tools

   and techniques logging, metrics, tracing.
• Exposure to

  AI concepts

   (basic understanding of ML model integration, AI-driven decisions, etc.).
• Troubleshoot and optimize application performance and data flows in production environments