Kafka Platform Architect – Real-Time Streaming (On-site)

Tap Growth ai; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Tap Growth ai in Singapore is seeking a Kafka Solution Engineer to design, implement, and support scalable real‑time streaming platforms. You will work closely with data engineering, architecture, and DevOps teams in enterprise environments to deliver robust Kafka-based solutions.

The role emphasizes hands‑on Kafka architecture, cloud deployment, and containerized operations using Kubernetes, Docker, Terraform, and Ansible.

Qualifications

• Bachelor's degree in Computer Science or related field.
• 4+ years hands-on with Apache Kafka or equivalents.
• Experience with enterprise-scale data streaming and distributed systems.
• Customer-focused and proactive delivery mindset.

Responsibilities

• Design, implement, and manage Kafka platforms and streaming solutions.
• Support topology and cluster management, configuration, and reliability.
• Deploy Kafka platforms across cloud and containerized environments.
• Develop real-time data pipelines and integrations.
• Implement infrastructure using Kubernetes, Docker, Terraform, and Ansible.
• Support CI/CD and automated deployment for Kafka components.
• Monitor, troubleshoot production issues and ensure security best practices.
• Collaborate with Data Engineers, Solution Architects, DevOps, and other teams.
• Provide technical guidance and contribute to solution design and documentation.

Skills

Kafka experience

Java / Python / Scala

Event-driven architecture

Cloud deployment

Docker

Kubernetes

CI/CD

Troubleshooting

Kafka components

Security best practices

Education

Bachelor's degree in Computer Science, Information Technology, Engineering

Tools

Terraform

Ansible

Job description

Tap Growth ai in Singapore is seeking a Kafka Solution Engineer to design, implement, and support scalable real‑time streaming platforms. You will work closely with data engineering, architecture, and DevOps teams in enterprise environments to deliver robust Kafka-based solutions.

The role emphasizes hands‑on Kafka architecture, cloud deployment, and containerized operations using Kubernetes, Docker, Terraform, and Ansible.