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Senior Kafka Engineer

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Enormous Enterprise

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Location:
United States , Tempe

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Contract Type:
Not provided

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Salary:

Not provided

Job Description:

Experienced Kafka Engineer with expertise in Confluent Kafka, Java/Scala, and distributed systems. Skilled in designing scalable, fault-tolerant Kafka-based data pipelines, troubleshooting messaging issues, and optimizing performance. Strong background in cloud deployments, microservices, and Agile development with an automate-first approach.

Job Responsibility:

  • Identify and rectify Kafka messaging issues within justified time
  • Work with the business and IT team to understand business problems and design, implement, and deliver an appropriate solution using Agile methodology across the larger program
  • Work independently to implement solutions on multiple platforms (DEV, QA, UAT, PROD)
  • Provide technical direction, guidance, and reviews to other engineers working on the same project
  • Administer distributed Kafka clusters in Dev, QA, UAT, and PROD environments and troubleshoot performance issues
  • Implement and debug subsystems/microservices and components
  • Follow an automate-first/automate-everything philosophy
  • Hands-on in programming languages

Requirements:

  • 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
  • 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

Nice to have:

Kafka Streams API (optional): Knowledge of Kafka Streams for real-time data processing within the Kafka ecosystem

Additional Information:

Job Posted:
January 12, 2026

Work Type:
On-site work
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