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CloudMile Linkedin · Posted 25d ago

Data Platform Engineer

Federal Territory of Kuala Lumpur

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Indexed description

About the Role

We are looking for a Data Platform Engineer to support the day-to-day stability, performance, and reliability of enterprise data platforms in production.

This role focuses on hands-on troubleshooting, operational support, and platform maintenance, working under the guidance of senior data engineers, architects, and SRE teams.

You will support data pipelines, data warehouses, analytics platforms, and selected AI/ML services, ensuring issues are resolved efficiently and systems operate reliably in a production environment.



Key Responsibilities

Production Support & Incident Handling

  • Act as an advanced support engineer for Data Platform incidents escalated from L1
  • Troubleshoot and resolve medium-complexity production issues
  • Participate in incident response activities, including:
  • Log analysis and diagnostics
  • Root cause identification
  • Minor code or configuration fixes
  • Fix validation and post-fix monitoring
  • Escalate complex or systemic issues to Engineering or Architecture teams with clear findings and evidence
  • Assist in post-incident reviews and documentation
  • Create and maintain operational handbooks, runbooks, and SOPs
  • [Bonus] Develop monitoring, alerting, or process automation tools to improve operational efficiency



Platform Operations & Reliability

  • Monitor health, performance, and availability of:
  • Data pipelines and orchestration workflows
  • Data warehouses and data lakes
  • Analytics and reporting platforms
  • Perform routine operational tasks, including:
  • Job restarts and failure recovery
  • Data quality checks and validations
  • Query or pipeline performance tuning
  • Operational and configuration-level fixes
  • Support platform stability improvements by following and enhancing existing runbooks and SOPs



Troubleshooting & Support

  • Investigate issues across:
  • Batch and streaming data pipelines
  • SQL queries and data models
  • APIs and data platform services
  • Assist with analysis of:
  • Query performance degradation
  • Data latency or freshness issues
  • Cost anomalies or resource over-utilization
  • Follow, update, and improve troubleshooting guides and operational documentation



Collaboration & Knowledge Sharing

  • Work closely with:
  • L1 support engineers
  • SRE teams
  • Delivery and project teams during solution handover
  • Support project-to-operations transition and production acceptance activities
  • Contribute to internal documentation and shared knowledge base
  • Share recurring issues, patterns, and learnings with the wider engineering team



Required Skills & Experience

Core Requirements

  • 2–4 years of experience in:
  • Data engineering
  • Data platform operations
  • Cloud or analytics support roles
  • Hands-on experience with:
  • Cloud platforms (GCP / AWS / Azure)
  • Data warehouses and data lakes
  • Batch and/or streaming data pipelines
  • Strong SQL skills for:
  • Data validation
  • Issue investigation
  • Performance analysis
  • Experience troubleshooting:
  • Failed data jobs
  • Pipeline errors
  • Data inconsistencies



Platform & Technical Skills

  • Familiarity with:
  • Data orchestration and workflow tools
  • API- and microservice-based platforms
  • Logging, monitoring, and alerting tools
  • Basic understanding of:
  • Distributed systems concepts
  • Cloud infrastructure components



Exposure to AI / Advanced Workloads (Nice to Have)

  • Exposure to supporting:
  • AI / ML pipelines
  • GenAI or inference services
  • Basic understanding of:
  • AI job execution and dependencies
  • Model inference latency considerations
  • Data inputs and outputs for AI workloads



Nice to Have

  • Experience with:
  • Containerized or serverless workloads
  • CI/CD pipelines for data platforms
  • Awareness of:
  • Cost monitoring or FinOps concepts
  • IAM and access control in cloud environments
  • Prior experience in:
  • Managed services
  • Customer-facing support or operations roles



Working Style & Mindset

  • Hands-on and detail-oriented
  • Comfortable working with operational processes and runbooks
  • Calm and methodical during production incidents
  • Willing to learn and grow into deeper platform and engineering responsibilities
  • Clear and structured communicator when escalating issues


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