Design, provision, and manage Apache Kafka clusters (self-managed on GCP/AWS or via Confluent Platform / MSK).
Configure and tune brokers, ZooKeeper/KRaft, topics, partitions, replication factors, and retention policies for high throughput and low latency.
Perform cluster upgrades, rolling restarts, and broker replacements with zero downtime.
Implement and manage Kafka Connect pipelines for data ingestion and egress across heterogeneous systems.
Administer Kafka Streams and ksqlDB deployments for real-time stream processing workloads.
Maintain Schema Registry and enforce schema governance standards across teams.
Define and track SLIs/SLOs for consumer lag, throughput, end-to-end latency, and broker health.
Design and implement cloud infrastructure using IaC – Terraform
Build automated deployment pipelines for Kafka configuration changes using GitOps workflows (ArgoCD, Flux).
Create self-service tooling and runbooks to reduce toil for development teams.
Automate topic provisioning, ACL management, and schema registration via APIs and CLI tooling.
Integrate tools like GitLab CI/CD , or Cloud Build for automated testing and deployment.
Ensure seamless integration of data pipelines with other GCP services like Big Query, Cloud Storage.
Monitor and Optimize performance, reliability, and cost of Kafka and streaming pipelines.
Implement security best practices for GCP resources, including IAM policies, encryption, and network security.
Ensure Observability is an integral part of the infrastructure platforms and provides adequate visibility about their health, utilization, and cost.
Collaborate extensively with cross functional teams to understand their requirements; educate them through documentation/trainings and improve the adoption of the platforms/tools.

Requirements

10+ years of overall experience in DevOps cloud engineering, or data engineering.
5+ years of experience in Kafka at production scale.
Deep expertise in Kafka internals: replication protocol, log compaction, consumer group coordination, partition leadership, and KRaft mode
Proficiency with container orchestration (Kubernetes / Helm) and deploying Kafka via Strimzi, Confluent Operator, or equivalent
Strong understanding of networking (VPC, peering, private endpoints, DNS, load balancing) in cloud environments.
Hands-on experience with Kafka Connect, Schema Registry, and at least one stream processing framework (Kafka Streams, Flink, Spark Structured Streaming).
Proficiency in Google Cloud Platform (GCP) services, including Dataflow, Pub/Sub, Kafka, Dataproc, Big Query, and Cloud Storage.
Expertise in Infrastructure as Code (IaC) tools like Terraform or Cloud Deployment Manager.
Familiarity with data orchestration tools like Apache Airflow or Cloud Composer.
Experience with CI/CD tools like Jenkins, GitLab CI/CD, or Cloud Build.
Knowledge of containerization and orchestration tools like Docker and Kubernetes.
Strong scripting skills for automation (e.g., Bash, Python).
Experience with monitoring tools like Cloud Monitoring, Prometheus, and Grafana.
Familiarity with logging tools like Cloud Logging or ELK Stack.
Strong problem-solving and analytical skills.
Excellent communication and collaboration abilities.
Ability to work in a fast-paced, agile environment.

Benefits

Health insurance
401(k) matching
Flexible work hours
Paid time off

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Apache KafkaKafka ConnectKafka StreamsksqlDBTerraformKubernetesDockerBashPythonCI/CD

Soft Skills

problem-solvinganalytical skillscommunicationcollaborationagile environment