Kafka Engineer - Monitoring Tools

We are looking for a skilled Kafka Engineer with 57 years of experience in designing, building, and maintaining real-time streaming pipelines using Apache Kafka. The Kafka Engineer will have strong expertise in Java-based development, Kafka architecture, and CI/CD integration. Youll play a key role in enabling real-time data processing and ensuring the scalability, fault tolerance, and governance of data streaming across our enterprise systems.

Key Responsibilities :

- Design and maintain Kafka-based streaming pipelines for high-throughput, low-latency real-time data processing.

- Ensure scalability, fault tolerance, and schema governance using tools like Schema Registry (Avro/Protobuf).

- Develop robust Kafka producers and consumers using Java, adhering to performance and reliability standards.

- Collaborate with DevOps teams to automate CI/CD pipelines, deployment, and infrastructure provisioning for Kafka components.

- Implement security best practices including encryption, authentication, and access control for Kafka clusters.

- Monitor and troubleshoot Kafka cluster health, latency, throughput, and message delivery

guarantees.

- Document architecture, deployment strategies, and operational runbooks for Kafka-based systems.

- Participate in code reviews, knowledge-sharing sessions, and architectural discussions.

Must-Have Skills :

- 5 - 7 years of experience in backend or data engineering, with strong focus on Apache Kafka.

- Proficiency in Java for building Kafka producers/consumers and integration with backend services.

- Deep understanding of Kafka internals (brokers, partitions, consumer groups, offsets, replication, etc.).

- Experience with schema management using Confluent Schema Registry, Avro, or Protobuf.

- Experience with CI/CD pipelines for Kafka component deployment and integration.

- Strong collaboration skills with DevOps teams to manage Kafka infrastructure, security, and

automation.

- Solid understanding of real-time data processing concepts, fault tolerance, and data consistency.

Good-to-Have Skills :

- Experience with Kafka Streams, ksqlDB, or Apache Flink for stream processing.

- Familiarity with Kafka Connect and connectors for data ingestion and export.

- Exposure to Confluent Kafka Platform and Kafka REST Proxy.

- Experience with monitoring and observability tools (e.g., Grafana, ELK Stack).

- Understanding of container orchestration platforms like Kubernetes or OpenShift.

- Knowledge of cloud-native Kafka deployments (AWS MSK).

- Familiarity with Spring Boot for integrating Kafka in microservice environments.