Data platform engineer - Financial Services

Michael Page International (HK) Ltd; Hong Kong; On-site; HKD 420,000 - 660,000; Full time

Job summary

Michael Page International (HK) Ltd in Hong Kong is seeking a Data Platform Engineer to manage and optimise data platforms within the Financial Services sector. The role is based in the Central District and offered on a temporary basis, providing a hands-on opportunity to apply technical expertise in a critical technology-focused environment.

You will support Data Lake and Data Pipeline platforms, troubleshoot workflows, and collaborate with data engineers and infrastructure teams on

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 Apache Spark and Apache Airflow.
• Experience troubleshooting data processing and workflow issues.
• Familiarity with cloud-based infrastructure and data platforms.
• Understanding of production support and system monitoring practices.
• Knowledge of Kubernetes (K8s) and Docker is highly preferred.
• Exposure to cloud-to-on-premises migration or transformation projects is advantageous.
• Strong analytical and problem-solving skills.
• Ability to work effectively with cross-functional technical teams.

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 Eng

Data Platform Ops

Apache Spark

Apache Airflow

Kubernetes

Docker

Cloud Infra

Data Lakes

Data Pipelines

Troubleshooting

Tools

Kubernetes

Docker

Job description

As a Data Platform Engineer in the Financial Services industry, you will play a key role in managing and optimising data platforms for efficient and secure operations. Based in the Central District, this temporary position offers a rewarding opportunity to apply your technical skills in a critical technology-focused role.

Our client is a well-established organisation undergoing data platform transformation initiatives.

Description

• 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

Profile

• 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 Apache Spark and Apache Airflow
• Experience troubleshooting data processing and workflow issues
• Familiarity with cloud-based infrastructure and data platforms
• Understanding of production support and system monitoring practices
• Knowledge of Kubernetes (K8s) and Docker is highly preferred
• Exposure to cloud-to-on-premises migration or transformation projects is advantageous
• Strong analytical and problem-solving skills
• Ability to work effectively with cross-functional technical teams

Job Offer

• Competitive salary package with stable career progression
• Opportunity to work on large-scale data platform transformation projects
• Exposure to modern data engineering and container technologies