Senior Platform Data Engineering

Role: Senior Data Platform Engineering (Cloud, AWS, & Snowflake)
Location: Kuala Lumpur, Malaysia

We are partnering with a leading telecom organization to hire a Senior Data Platform Engineer to support and enhance its enterprise data platform. This role will focus primarily on execution and engineering delivery (70%), with partial ownership (30%) of platform components across AWS and Snowflake environments.

The incumbent will work closely with platform leads, data engineering, and infrastructure teams to ensure the stability, performance, and continuous improvement of the cloud-based data ecosystem.

• Support day-to-day operations of the cloud data platform across AWS and Snowflake (DEV/SIT/PROD environments).
• Implement and maintain cloud infrastructure components in AWS (S3, EC2, Lambda, IAM).
• Support Snowflake administration tasks including user access management, warehouse monitoring, and performance optimization.
• Assist in CI/CD pipeline implementation and automation of deployment processes.
• Monitor platform health, resolve incidents, and contribute to root cause analysis and performance improvements.
• Collaborate with data engineers to support data ingestion, transformation, and platform integration activities.
• Participate in security and governance enforcement aligned with cloud and data compliance standards.
• Contribute to documentation, operational playbooks, and continuous improvement initiatives.
  
  

5-6 years of experience in cloud engineering, data platform engineering, or data infrastructure roles.

Working experience with AWS services such as S3, EC2, Lambda, and basic IAM configurations.

Hands-on experience as a Snowflake user (query optimization, warehouse usage, role-based access understanding).

Exposure to DevOps practices, CI/CD pipelines, or infrastructure-as-code tools is an advantage.

Basic understanding of monitoring and logging tools (e.g., CloudWatch or similar).

Familiarity with data engineering workflows and cloud-based data architectures.

Experience supporting production environments and participating in incident management.

Strong problem-solving skills and ability to work independently as an individual contributor.

• Exposure to SageMaker or ML platform environments (not mandatory).
• Experience with containerized environments or orchestration tools.
• Knowledge of data governance or compliance frameworks.

• 70% hands-on execution and engineering delivery
• 30% component-level ownership and platform improvement
• Individual contributor role (no people management)
• Opportunity to grow into broader platform ownership over time