Senior Big Data Engineer (Compute & Transformation) – Contract

The client is a Singapore-based data consultancy seeking a hands-on Senior Infrastructure Engineer to deploy and operate the compute and transformation layer of a large-scale on-premise data platform.

This is an initial contract position, with the potential for extension or conversion to a permanent position based on business requirements and individual performance.

·   Design, deploy and operate distributed compute, query and transformation services in an on-premise or hybrid environment.

·   Containerise platform components using Docker and deploy and operate production workloads on Kubernetes.

·   Build and support large-scale processing and query services using Spark, Trino and ClickHouse.

·   Develop and maintain governed transformation workflows using dbt.

·   Integrate compute services with Apache Iceberg tables and Apache Polaris catalogues.

·   Tune workload performance, resource allocation, concurrency and reliability for terabyte- or petabyte-scale data.

·   Implement monitoring and logging using VictoriaMetrics and VictoriaLogs or comparable observability tools.

·   Troubleshoot distributed-system, workload, storage-integration and production-performance issues.

·   Produce technical documentation, operating procedures and deployment runbooks.

·   Work directly with technical stakeholders and contribute as a senior individual contributor.

Requirements

·   Minimum six years of hands-on experience in data-platform, big-data infrastructure, distributed systems or a closely related role.

·   Production experience with both Docker and Kubernetes is mandatory.

·   Strong experience deploying and operating distributed data workloads in on-premise or hybrid environments.

·   Hands-on experience with distributed compute and query technologies such as Spark, Trino and ClickHouse.

·   Practical experience with data transformation and lakehouse technologies including dbt, Apache Iceberg and Apache Polaris.

·   Experience monitoring platform workloads through VictoriaMetrics, VictoriaLogs or comparable technologies.

·   Strong understanding of Linux, networking, resource management, performance tuning, high availability and recovery.

·   Experience supporting high-volume platforms at terabyte or petabyte scale.

·   Ability to operate independently and communicate effectively with client and technical stakeholders.

·   Willingness to accept a six-to-twelve-month contract and attend client locations when required.

·   Data-platform delivery within regulated sectors such as banking, fintech, healthcare or data centres.

·   Experience with Kubernetes Operators, Helm, CI/CD and infrastructure automation.

·   Experience integrating compute engines with distributed storage such as Ceph.

This position focuses on the compute and transformation infrastructure of a data platform. It is not primarily a business-intelligence, dashboarding, visualisation or data-analyst role.

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]

See your resume through a recruiter's eyes. Get a FREE PathSource Resume Score and review report to understand how your resume may be coming across and what you can improve next.

Submit your resume for a free review and, with your consent, join PathSource Consulting's talent network to be considered for suitable future opportunities.

resume.path-source.com

Optional career resource only. Participation is not required and does not affect consideration for this vacancy.

Please indicate the following information in your resume:

·   Current and expected salary

·   Reason or reasons for leaving

·   Availability to commence work

By submitting an application or resume to us, you consent to PathSource Consulting collecting, using, retaining and disclosing your personal information to prospective employers for recruitment purposes.

Skills

Snowflake Cloud Data Warehouse, Distributed Database, Service Transformation, Distributed Processing, Adobe Spark, Design, Apache Spark, Storage Architecture, ClickHouse, Log Management, Workflow Development, managing workload, Resource Allocation, Hands-On Experience, Infrastructure, Data Infrastructure, Docker Container