Kafka Troubleshooter- Deep understanding of Kafka architecture: Thorough knowledge of how Kafka components like brokers, topics, partitions, consumer groups, and replication factors work together. Log analysis: Ability to interpret Kafka logs from producers, consumers, and brokers to identify error messages, warnings, and potential issues. Monitoring and metrics: Familiarity with monitoring tools to track key Kafka metrics like consumer lag, message throughput, broker CPU usage, and network latency. Distributed systems knowledge: Understanding of concepts like fault tolerance, data replication, leader election, and distributed consensus to troubleshoot issues related to cluster failures. Programming language proficiency: Strong coding skills in Java or Scala, as many Kafka applications are written in these languages, allowing you to debug custom producers and consumers. Network troubleshooting: Ability to diagnose network connectivity issues between brokers and clients, including checking network configurations and firewall rules. Kafka configuration management: Knowledge of Kafka configuration parameters, including topic creation, partition settings, replication factors, and consumer group settingsDeveloper- Deep understanding of Confluent Kafka: Thorough knowledge of Kafka concepts like producers, consumers, topics, partitions, brokers, and replication mechanisms. Programming language proficiency: Primarily Java or Scala, with potential for Python depending on the project. System design and architecture: Ability to design robust and scalable Kafka-based data pipelines, considering factors like data throughput, fault tolerance, and latency. Data management skills: Understanding of data serialization formats like JSON, Avro, and Protobuf, and how to manage data schema evolution. Kafka Streams API (optional): Knowledge of Kafka Streams for real-time data processing within the Kafka ecosystem. Monitoring and troubleshooting: Familiarity with tools to monitor Kafka cluster health, identify performance bottlenecks, and troubleshoot issues. Cloud integration : Experience deploying and managing Kafka on cloud platforms like AWS, Azure, or GCP. Distributed systems concepts: Understanding of concepts like distributed consensus, leader election, and fault tolerance. Security best practices: Knowledge of Kafka security features to implement authentication and authorization mechanisms. Communication and collaboration: Ability to work effectively with other developers, data engineers, and stakeholders to design and implement Kafka solutions. Strong Experience with Kafka connect / KSQL architecture and associated clustering model. Hands on experience with Kafka Db connector for Oracle, Mysql. Strong fundamentals and experience in Kafka administration, configuration, and troubleshooting. Understand and experience with Kafka clustering, and its fault-tolerance model supporting HA and DR. Have developed
Diverse Lynx LLC is an Equal Employment Opportunity employer. All qualified applicants will receive due consideration for employment without any discrimination. All applicants will be evaluated solely on the basis of their ability, competence and their proven capability to perform the functions outlined in the corresponding role. We promote and support a diverse workforce across all levels in the company.