Java Developer with AWS EKS
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Java Developer With AWS EKSRequired Technical Skill SetCore Java: OOPs, Design Patterns, Interface, SerializationORM: Hibernate, Java, OpenJPAJava Build Tools: Maven, Gradle, ANTWeb Technologies: CSS, HTML, JQuery, JavaScript, AJAXJava Web Frameworks: SpringMVCSOAP & REST WebservicesApplication Containers: JBoss, Jetty, WebSphere, WebLogicJava Testing Tools: JUnit, TestNG, SeleniumJava EE Components: Servlets, Java Beans (EJB), Java Server Pages (JSP)Code Version Control: GitHubHands-on Software Development experience in JavaHands on experience in designing and developing applications using Java EE platformsObject Oriented analysis and design using common design patterns.Excellent knowledge of Relational Databases, Oracle, SQL and DB2Experience in the Spring FrameworkUnderstanding of key AWS services relevant to EKS deployments, including EC2, VPC, IAM, S3, RDS, CloudWatch, and potentially others like Lambda or DynamoDBStrong grasp of Kubernetes concepts, including Pods, Deployments, Services, Ingress, Namespaces, and kubectl commands.Specific knowledge of how to deploy, manage, and scale applications on Amazon Elastic Kubernetes Service (EKS). This includes understanding EKS architecture, networking, and integration with other AWS services.Proficiency with Docker for containerizing Java applications.Experience with Continuous Integration and Continuous Deployment (CI/CD) pipelines using tools like Jenkins, AWS CodePipeline, or GitLab CI/CD, specifically for deploying applications to EKS.Familiarity with IaC tools like AWS CloudFormation or Terraform for provisioning and managing EKS clusters and related infrastructure.Understanding of security best practices within AWS and Kubernetes, including IAM roles, network security groups, and pod security policies.Experience with monitoring and logging solutions for EKS, such as CloudWatch, Prometheus, Grafana, or ELK stack.Comprehensive understanding of Kafka's core components (producers, consumers, brokers, topics, partitions, Zookeeper).Experience with Kafka Connect for integrating Kafka with other data systems and Kafka Streams for building real-time stream processing applications.Knowledge of managing and monitoring Kafka clusters, including performance tuning and troubleshooting.Understanding and implementation of Schema Registry for managing data schemas in Kafka-based systems.