Kafka Engineer at Maveric Systems Limited in Irving, Texas

Posted in Other 3 days ago.

Type: full-time





Job Description:

Role - Kafka Engineer

Job Type- Full Time

Location- Irving, TX

We are seeking a skilled Kafka Engineer to join our team. The ideal candidate will be responsible for designing, implementing, and supporting Kafka clusters to facilitate real-time data processing within our organization.

Responsibilities:
  • Design, deploy, and manage Kafka clusters to ensure high availability, scalability, and performance.
  • Collaborate with cross-functional teams to integrate Kafka into existing systems and applications.
  • Monitor Kafka clusters and troubleshoot any issues that arise, ensuring timely resolution to minimize downtime.
  • Optimize Kafka configurations and performance to meet the organization's data processing requirements.
  • Implement security measures and best practices to safeguard Kafka clusters and data.
  • Provide guidance and support to development teams on Kafka-related tasks and projects.
  • Stay updated on the latest Kafka developments, trends, and best practices to continuously improve our Kafka infrastructure.
  • Document Kafka configurations, processes, and procedures for reference and training purposes.

Requirements:
  • Bachelor's degree in Computer Science, Engineering, or related field.
  • Proven experience working with Kafka in a production environment.
  • Strong understanding of Kafka architecture, concepts, and components.
  • Proficiency in Kafka administration, including cluster setup, configuration, and tuning.
  • Experience with Kafka monitoring, performance optimization, and troubleshooting.
  • Familiarity with Kafka security features and best practices.
  • Excellent communication and collaboration skills.
  • Ability to work independently and as part of a team in a fast-paced environment.

Preferred:
  • Certification in Kafka administration or development.
  • Experience with related technologies such as Apache Zookeeper, Apache Storm, and Apache Spark.
  • Knowledge of streaming data processing and messaging systems.
  • Familiarity with cloud platforms and containerization technologies.

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