6767 | Kafka Engineer

3 weeks ago

Bhavnagar, India EXL Full time

Job Title: Kafka Engineer (Java) Experience: 5–8 Years Job Summary: We are looking for a skilled Kafka Engineer with 5–7 years of experience in designing, building, and maintaining real-time streaming pipelines using Apache Kafka. The ideal candidate will have strong expertise in Java-based development, Kafka architecture, and CI/CD integration. You’ll 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

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