3-5 years of dedicated experience designing, building, and managing production Apache Kafka environments.
Expert proficiency in Java and the Spring Boot ecosystem, with specific, hands-on experience using the Spring for Apache Kafka framework.
Deep understanding of the Kafka architecture, including topics, partitions, brokers, producers, consumers, and the Zookeeper/KRaft protocol. . Hands-on experience with the Kafka ecosystem, including Kafka Connect, Kafka Streams, and Schema Registry.
Proven experience in performance tuning of Kafka clusters and client applications.
Strong understanding of distributed systems concepts (e.g., fault tolerance, scalability, consistency).
Experience with cloud-native environments, including containerization (Docker) and orchestration (Kubernetes).
Familiarity with Infrastructure as Code (IaC) tools like Terraform or Ansible.
Relevant certifications, such as the Confluent Certified Developer for Apache Kafka (CCDAK).
Experience with stream processing frameworks like ksqlDB, Apache Flink, or Spark Streaming.
Design and architect robust, end-to-end streaming solutions. Define patterns and best practices for topic design, data partitioning, schema management, and fault tolerance.
Act as a hands-on backend engineer, developing and maintaining Kafka-native applications and microservices using Java and Spring Boot (specifically Spring for Apache Kafka). Implement custom producers, consumers, and stream processors.
Proactively monitor the Kafka cluster's health and performance. Lead efforts to identify and resolve bottlenecks, fine-tune broker configurations, and optimize client applications for throughput and latency.
Manage and configure the complete Kafka ecosystem, including Kafka Connect for data integration, Schema Registry for data governance, and other streaming components.
Establish and enforce best practices for Kafka usage across all engineering teams. Create documentation, provide guidance, and mentor other developers on building efficient and reliable streaming applications.
Implement and manage comprehensive monitoring, logging, and alerting for the Kafka infrastructure to ensure operational excellence and rapid issue resolution.
