Java Engineer

Required Technical Skill Set

Core Java: OOPs, Design Patterns, Interface, Serialization

ORM: Hibernate, Java, OpenJPA

Java Build Tools: Maven, Gradle, ANT

Web Technologies: CSS, HTML, JQuery, JavaScript, AJAX

Java Web Frameworks: SpringMVC

SOAP & REST Webservices

Application Containers: JBoss, Jetty, WebSphere, WebLogic

Java Testing Tools: JUnit, TestNG, Selenium

Java EE Components: Servlets, Java Beans (EJB), Java Server Pages (JSP)

Code Version Control: GitHub

Hands-on Software Development experience in Java

Hands on experience in designing and developing applications using Java EE platforms

Object Oriented analysis and design using common design patterns.

Excellent knowledge of Relational Databases, Oracle, SQL and DB2

Experience in the Spring Framework

Understanding of key AWS services relevant to EKS deployments, including EC2, VPC, IAM, S3, RDS, CloudWatch, and potentially others like Lambda or DynamoDB

Strong 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.