Data Platform Engineer: Data Lakes & Pipelines

Michael Page International (Hong Kong) Limited; Hong Kong; On-site; HKD 350,000 - 600,000; Full time

Benefits offered by this job

Competitive salary package

Exposure to modern data engineering &容

Opportunities to work on large-scale平台

Job summary

Michael Page International (Hong Kong) Limited is seeking a Data Platform Support professional to help maintain and optimise Data Lake and Data Pipeline environments. The role involves monitoring workflows, diagnosing issues, and collaborating with data engineers and infra teams on daily operations.

Ideal candidates have 2–4 years in data engineering or platform operations, with hands-on Spark and Airflow experience, and familiarity with cloud-to-on-premises migrations.

Qualifications

• 2-4 years of experience in Data Engineering, Platform Support, or Data Platform Operations.
• Hands-on experience supporting Data Lakes and Data Pipelines.
• Strong knowledge of Spark and Airflow.
• Familiarity with cloud-based infrastructure and data platforms; production support exposure.

Responsibilities

• Support and maintain enterprise Data Lake and Data Pipeline platforms
• Monitor, troubleshoot, and optimise data processing workflows
• Ensure platform stability, availability, and operational performance
• Collaborate with data engineers and infrastructure teams on daily support activities
• Assist in cloud-to-on-premises platform migration and transformation projects
• Support deployment, configuration, and maintenance of data platform environments
• Participate in incident resolution and root cause analysis
• Contribute to platform enhancements and operational improvements
• Work with containerisation and orchestration technologies in distributed environments

Skills

Data engineering

Data platform operations

Cross-functional collaboration

Analytical thinking

Tools

Apache Spark

Apache Airflow

Kubernetes

Docker

Job description

Michael Page International (Hong Kong) Limited is seeking a Data Platform Support professional to help maintain and optimise Data Lake and Data Pipeline environments. The role involves monitoring workflows, diagnosing issues, and collaborating with data engineers and infra teams on daily operations.

Ideal candidates have 2–4 years in data engineering or platform operations, with hands-on Spark and Airflow experience, and familiarity with cloud-to-on-premises migrations.