Java Technical Architect

Mandatory required skills : Core Java with SpringBoot and integration frameworks (messaging and streaming) such as Kafka

Preferred/Desired skills

Strong proficiency in Apache Kafka, including broker setup, topic management, and partitioning strategies.

Knowledge of data serialization formats such as Avro, Protobuf, and JSON.

Experience with Linux/Unix systems and scripting (Bash, Python, etc.).

Familiarity with DevOps practices and tools like Docker, Kubernetes, CI/CD pipelines, and Terraform.

Experience with monitoring tools (Prometheus, Grafana) and logging tools (Elasticsearch, Logstash, Kibana).

Please share the Detailed Job Description

Kafka Cluster Management: Design, deploy, and manage Apache Kafka clusters, ensuring high availability, scalability, and fault tolerance.

Data Streaming Architecture: Develop and maintain real-time data streaming solutions using Kafka, Kafka Streams, and related technologies.

Performance Optimization: Monitor and optimize Kafka clusters for performance, including tuning brokers, topics, partitions, and configurations.

Security and Compliance: Implement and manage Kafka security measures, including encryption, authentication, and authorization, to ensure data integrity and compliance with industry standards.

Integration: Work closely with application developers, data engineers, and DevOps teams to integrate Kafka with other systems and services.

Monitoring and Alerts: Use tools such as Prometheus, Grafana, and Kafka Manager to set up monitoring, logging, and alerting for Kafka clusters.

Troubleshooting and Support: Diagnose and promptly resolve issues related to Kafka performance, connectivity, and data processing.

Documentation: Create and maintain detailed documentation for Kafka configurations, processes, and best practices.

Innovation and Improvement: Stay up-to-date with the latest developments in Kafka and related technologies, proposing improvements and new solutions as appropriate.

Proven experience with distributed systems, data streaming, and event-driven architectures.

Experience with Kafka Streams, KSQL, and other Kafka ecosystem tools.

Hands-on experience with cloud platforms (AWS, Azure, Google Cloud) is a plus.