Senior Data Platform Engineer (Ingest & Storage) – Immediate Hiring

The client is a Singapore-based data consultancy seeking a hands-on Senior Data Platform Engineer to build and operate large-scale data ingestion and storage services in an on-premise or hybrid environment.

This is a contract role available for immediate hiring. Candidates who can commence at short notice are encouraged to apply. There may be potential for extension or conversion to a permanent position, subject to business requirements and individual performance. The role is based in Singapore. The hiring company is currently located in MacPherson, and work at or travel to client sites may be required. Final work location and arrangements will be confirmed.

JOB DESCRIPTION

We are looking for an experienced Data Platform Engineer to help build and operate a modern data platform. This is a contract role suited to someone who enjoys working with large-scale data ingestion, distributed storage and cloud-native infrastructure.

The role involves technologies such as Kafka, Ceph, Apache Iceberg, Docker and Kubernetes. Experience with every listed tool is not expected, but candidates should have strong hands-on experience in the core areas and be comfortable working with related technologies.

Key Responsibilities

• Build and support batch and streaming data-ingestion solutions using Kafka or comparable technologies.
• Deploy and operate data-platform workloads using Docker and Kubernetes.
• Support distributed storage and lakehouse services, including Ceph or comparable technologies and Apache Iceberg.
• Integrate platform components such as catalogues, ingestion frameworks and observability tools.
• Monitor platform reliability, troubleshoot production issues and contribute to performance tuning and recovery.
• Prepare technical documentation, operating procedures and deployment runbooks.

Requirements

• Relevant hands-on experience in data engineering, data platforms, infrastructure engineering or a closely related role.
• Production experience with both Docker and Kubernetes is mandatory.
• Practical experience with Kafka or another data-ingestion or streaming platform.
• Experience with Ceph or another distributed-storage technology, and Apache Iceberg or a comparable lakehouse/data-lake environment.
• Experience deploying or supporting platforms in on-premise or hybrid environments is preferred.
• Able to explain the platform components you have personally built, deployed or supported.
• Comfortable working on a contract basis and attending client locations when required.

Preferred Experience

• Experience with Apache Polaris, dltHub, VictoriaMetrics or VictoriaLogs.
• Experience supporting large-scale data environments, including terabyte- or petabyte-scale platforms.
• Experience with Kubernetes Operators, Helm, CI/CD or infrastructure automation.

This position focuses on ingestion and storage infrastructure. It is not primarily a business-intelligence, dashboarding, visualisation or data-analyst role.

ADDITIONAL INFORMATION

This is a contract role available for immediate hiring. Candidates who can commence at short notice are encouraged to apply. There may be potential for extension or conversion to a permanent position, subject to business requirements and individual performance.

The role is based in Singapore. The hiring company is currently located in MacPherson, and work at or travel to client sites may be required. Final work location and arrangements will be confirmed.

HOW TO APPLY

Submit your application by emailing your updated resume in MS Word format to:

Wills Heng Wei He
EA Personnel Registration No. R1549842
Email: [email protected]

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FOR IMMEDIATE CONSIDERATION

Please indicate the following information in your resume:

• Current and expected salary
• Reason or reasons for leaving
• Availability to commence work

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Skills

Data Ingestion, Distributed Platforms, storage facilities, Kubernetes, computer components, Preparation of Technical Documents, Cloud Storage, Troubleshooting Performance Issues, Production Deployment, Apache Kafka, Content Ingest Operations, Streaming Media, Data Infrastructure, Cataloging, Docker Container, Infrastructure Design