Job Summary
We are seeking a Kafka Solution Engineer with strong hands-on experience in Kafka architecture, platform engineering, and cloud deployment. The ideal candidate will design, implement, and support scalable real-time streaming platforms, working closely with data engineering, architecture, and DevOps teams in enterprise environments.
Key Responsibilities
- Design, implement, and manage Apache Kafka platforms and streaming solutions.
- Support Kafka architecture, cluster management, configuration, performance, and reliability.
- Deploy and manage Kafka platforms across cloud and containerized environments.
- Develop and maintain real-time data pipelines and integrations.
- Implement and manage infrastructure using Kubernetes, Docker, Terraform, and Ansible.
- Support CI/CD processes and automated deployment of Kafka and platform components.
- Monitor, troubleshoot, and resolve Kafka and platform-related production issues.
- Implement security, access control, monitoring, and operational best practices.
- Collaborate with Data Engineers, Solution Architects, DevOps, and other technical teams.
- Provide technical guidance and contribute to solution design and documentation.
General Qualifications
- Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field.
- 4+ years of hands-on experience with Apache Kafka or equivalent Kafka distributions such as Confluent, Cloudera, or AWS MSK.
- Experience working with enterprise-scale data streaming, integration, or distributed systems.
- Customer-focused, proactive, and adaptable approach to technical delivery.
Mandatory Skills
- Apache Kafka – 4+ years of hands-on experience (particularly with Confluent Kafka).
- Strong proficiency in at least one programming language: Java, Python, or Scala.
- Good understanding of event-driven architecture and data streaming patterns.
- Experience deploying or managing Kafka on AWS, GCP, or Azure.
- Experience with Docker, Kubernetes, and CI/CD.
- Strong troubleshooting and problem-solving skills.
- Experience with Kafka components such as Kafka Connect, Kafka Streams, Schema Registry, or REST Proxy.
Nice-to-Have Skills
- Experience with Confluent Platform or Confluent Cloud.
- Experience with ksqlDB, Apache Flink, or Confluent for Kubernetes (CFK).
- Knowledge of Kafka KRaft, multi-cloud deployments, and Kafka security.
- Experience with Prometheus, Grafana, or Splunk.
- Experience with data lakes, data warehouses, or big data platforms.
- Confluent certifications such as Confluent Developer, Administrator, or Flink Developer.