Kafka Administrator
Mohd HameedUnited StatesSENIORPosted 46m ago
KafkaAWSMSKTerraformGitLabDatadogLinuxBashPython
About the Role
We are migrating a portfolio of Apache Kafka clusters from on-premises platforms to AWS MSK. We are looking for a senior, hands-on Kafka engineer to own day-to-day Kafka administration across both environments, drive the migration, and coordinate with producer and consumer application teams.
Key Responsibilities
• Administer and operate Kafka clusters across Cloudera, Confluent Platform, and AWS MSK
• Manage topics, partitions, replication, retention, quotas, ACLs, and consumer groups
• Tune brokers, producers, and consumers for throughput, latency, and reliability
• Handle patching, upgrades, capacity planning, and cluster health/performance troubleshooting
• Configure and maintain security: TLS/SSL, SASL, mTLS, IAM (for MSK), RBAC/ACLs, and encryption at rest and in transit
• Plan and execute migration of clusters and workloads from on-prem to AWS MSK
• Design cutover strategies with minimal downtime and no data loss
• Validate topic parity, offsets, throughput, and data integrity pre- and post-migration
• Define rollback plans and run migration dry-runs in lower environments
Requirements
• 5+ years in data/platform/infrastructure engineering, with 4+ years operating Apache Kafka in production
• Hands-on administration experience with Cloudera and Confluent Platform
• Production experience with AWS MSK (provisioning, configuration, IAM auth, networking)
• Proven experience migrating Kafka workloads to the cloud with minimal disruption
• Strong Terraform and GitLab CI/CD experience for infrastructure automation
• Hands-on Datadog experience for monitoring, dashboards, and alerting
• Deep understanding of Kafka internals: partitions, replication, ISR, offsets, consumer groups, and delivery semantics
• Solid AWS fundamentals: VPC, security groups, IAM, KMS, CloudWatch, PrivateLink
• Strong Linux, networking, and scripting skills (Bash, Python)
• Excellent communication and coordination skills to work across producer/consumer teams