Kafka Platform Engineer

Required Skills

• Strong hands-on experience with Apache Kafka / Confluent Kafka (3+ years):
  

Cluster installation and administration.
Topic management, partitioning, replication.
Quotas, ACL management.

• Experience with:
  

Kafka Connect (connector development/configuration).
ksqlDB or Kafka Streams.
Schema Registry (Avro, Protobuf, JSON).

• Kafka monitoring and performance tuning:
  

Prometheus, Grafana, JMX, Kafka Metrics.

• Incident response in production Kafka environments.
  
• Basic Kubernetes/OpenShift experience:
  

Kafka deployment in containerized environments.

• Networking and security knowledge:
  

TLS/SSL, Kerberos, SASL.

Nice-to-Have Skills

• GitOps automation: ArgoCD, Flux, Helm Charts, CRDs.
  
• Infrastructure as Code (IaC): Terraform for Cloud and Kubernetes.
  
• Hybrid cloud experience (Azure + On-Premises).
  
• Container security frameworks: OPA, Kyverno, image scanning.
  
• Disaster Recovery (DR) and High Availability (HA) strategies:
  

Raft Mode, ZooKeeper-Free Kafka, MirrorMaker.

• Kafka capacity and cost optimization:
  

Dynamic scaling, tiered storage. ,[Design, deploy, and operate scalable Apache Kafka clusters (on-premises, Cloud, OpenShift)., Configure and maintain Kafka components: (Kafka Brokers (setup, monitoring, scaling); Kafka Connect (connectors, integrations); ksqlDB (stream processing); Schema Registry (schema management, compatibility); MirrorMaker (cross-cluster replication))., Implement authentication and security: (TLS/SSL, SASL/SCRAM, ACLs (access control); Kerberos (enterprise authentication integration))., Monitor and optimize performance: (Metrics collection via Prometheus, Grafana, JMX, Kafka Metrics; Bottleneck identification, tuning (partitioning, replication factor, quotas))., Incident management: (Rapid response, root cause analysis (RCA), system recovery; Post-mortem documentation and preventive recommendations)., Automate infrastructure: Infrastructure as Code (IaC) and GitOps for Kafka deployments., Capacity planning: Performance and scalability optimization (partitioning, tiered storage, dynamic scaling)., Architectural support: Contribute to platform architecture decisions related to Kafka., Documentation and knowledge sharing: Create technical documentation, best practices, and training materials for ops and dev teams.] Requirements: Kafka, Kubernetes, OpenShift, GitOps, IaC