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Home/Jobs/Kafka Engineer
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Devsinc

Kafka Engineer

šŸ‡øšŸ‡¦ Riyadh, Saudi ArabiašŸ¢ On-site
KafkaConfluent KafkaZooKeeperSchema RegistryPrometheusJMX ExporterElasticTLS
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Devsinc is looking for a knowledgeable and enthusiastic Kafka Engineer to join our growing team in KSA. In this role, you will be responsible for designing, implementing, and managing Kafka-based data pipelines and stream processing systems. You will work with cross-functional teams to integrate Kafka with different systems and ensure data flow reliability and efficiency.

Requirements

Requirements:

Kafka Operations: Confluent Kafka ; cluster setup and maintenance.
Cluster Management: High availability, cross-site replication,ZooKeeper.

Schema Registry & Topic Governance: Confluent Schema Registry or equivalent.

Monitoring: Prometheus JMX Exporter, Dynatrace Kafka plugins, Elastic. Security: TLS, SASL, ACLs, RBAC.

Integration & APIs: Kafka REST API, connectors.

Key Responsibilities:

Event-driven architecture and distributed system principles.

Performance tuning and throughput optimization.

Disaster recovery strategies for Kafka clusters.

Governance, schema evolution, and topic lifecycle management.

Operate and scale Kafka clusters reliably.

Ensure HA and cross-site replication.

Implement governance, topic management, and secure access.

Integrate and monitor Kafka metrics/logs into observability dashboards.

Ensure proper ACLs and RBAC policies for producers/consumers

Respond to Kafka-related incidents and outages

Experience: Minimum 4–6 years of experience required.

Requirements

  • •Kafka Operations (Confluent Kafka, cluster setup/maintenance)
  • •Cluster Management (High availability, cross-site replication, ZooKeeper)
  • •Schema Registry/Topic Governance
  • •Monitoring tools (Prometheus, Dynatrace, Elastic)
  • •Security implementation (TLS, SASL, ACLs, RBAC)
  • •Integration APIs (Kafka REST API, connectors)

Responsibilities

  • •Event-driven architecture and distributed system principles
  • •Performance tuning and throughput optimization
  • •Disaster recovery strategies for Kafka clusters
  • •Governance, schema evolution, and topic lifecycle management
  • •Operate and scale Kafka clusters reliably
  • •Ensure HA and cross-site replication
  • •Implement governance, topic management, and secure access
  • •Integrate and monitor Kafka metrics/logs

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