Kafka Engineer Responsibilities: Design and develop robust, scalable, and efficient Kafka-based data pipelines, ensuring the smooth flow of data across systems and applications. Collaborate with cross-functional teams to integrate Kafka with other big data technologies, such as Hadoop, Spark, and Storm, to build comprehensive data processing and analytics solutions. Monitor and optimize Kafka clusters for performance, reliability, and scalability, ensuring high throughput and low latency. Troubleshoot and resolve any issues related to Kafka, including performance bottlenecks, data replication, and cluster synchronization problems. Provide technical support and guidance to customers, addressing their queries and issues related to Kafka deployments and data pipelines. Develop and maintain documentation, including design specifications, best practices, and troubleshooting guides, to ensure proper usage and understanding of Kafka within the organization. Stay up to date with the latest developments in Kafka and other big data technologies, evaluating their potential impact and applicability to the existing data infrastructure. Collaborate with data architects, software engineers, and other stakeholders to define requirements, propose architectural improvements, and drive the adoption of Kafka and related technologies. Implement security measures and access controls to ensure data privacy and compliance with relevant regulations. Conduct performance testing and tuning exercises to optimize Kafka performance and scalability. Write efficient and maintainable code in Java or Python, following coding standards and best practices. Qualifications and Skills: Strong knowledge of Apache Kafka, including concepts such as topics, partitions, producers, consumers, and brokers. Proficiency in programming languages such as Java or Python, with experience in building distributed systems and working with big data technologies. Solid understanding of other big data technologies, including Hadoop, Spark, and Storm, and their integration with Kafka. Experience in monitoring and optimizing Kafka clusters, using tools like Kafka Manager, Prometheus, Grafana, or similar. Strong troubleshooting and problem-solving skills, with the ability to diagnose and resolve issues related to Kafka and data pipelines. Excellent communication and interpersonal skills, with the ability to work effectively in cross-functional teams and provide support to customers. Familiarity with data integration patterns, event-driven architectures, and real-time data processing concepts. Knowledge of security best practices and experience in implementing access controls and data encryption in Kafka environments. Experience with cloud platforms and technologies, such as AWS, Azure, or GCP, and their integration with Kafka, is a plus. Familiarity with containerization technologies like Docker and orchestration frameworks like Kubernetes is desirable. Bachelor's or Master's degree in computer science, engineering, or a related field.