AI-Driven Maintenance Planning Analyst

EDP APAC; Singapore; On-site; SGD 70,000 - 110,000; Full time

Benefits offered by this job

Flexible work conditions

Remuneration competitive with market

Personal and professional development

Job summary

EDP APAC, headquartered in Singapore, seeks a Maintenance Programme Analyst to independently develop and control the solar asset portfolio's maintenance programme. You will convert preventive and corrective maintenance needs into optimised work-orders for execution by clusters.

You will govern maintenance backlog, validate completion data and apply analytics and AI-assisted models to improve prioritisation, resource planning and maintenance performance.

Qualifications

• Bachelor’s degree in Engineering, Data Analytics or related field.
• 1–2 years of experience in maintenance engineering, operations, maintenance planning or asset management within power/renewable-energy or similar asset-intensive sector.
• Experience developing preventive, predictive and corrective maintenance programmes.
• Experience analysing maintenance histories, failure patterns, asset-criticality, backlog and asset-performance information.
• Practical experience with computerised maintenance-management or enterprise asset-management systems, including maintenance plans, job plans, work orders and asset master data.
• Experience coordinating maintenance requirements with engineering, operations, contractors, OEMs and procurement teams.
• Experience with digitalisation, automated reporting or AI-enabled maintenance applications would be advantageous.
• Strong knowledge of preventive, predictive, condition-based and corrective maintenance principles.
• Ability to develop risk-based maintenance programmes using equipment criticality, asset condition and engineering requirements.
• Proficiency in maintenance planning, scheduling, backlog management and work-readiness assessment.
• Advanced working knowledge of maintenance-management systems, asset master data and maintenance records.
• Strong analytical capability to identify failure trends, evaluate programme effectiveness and recommend maintenance improvements.

Responsibilities

• Develop annual, quarterly, monthly and weekly maintenance programmes for the solar asset portfolio.
• Establish preventive maintenance activities and frequencies based on equipment requirements, contracts, regulations, asset criticality and operating experience.
• Consolidate corrective maintenance triggers received from Monitoring, Asset Management, Technical Engineers and Cluster Leads.
• Include shutdown windows, site-access restrictions, statutory deadlines and known resource constraints in the programme.
• Maintain a forward forecast of workload, manpower, contractor and material requirements.
• Develop and maintain a transparent prioritisation model considering safety, asset availability, equipment criticality, contractual obligations etc.
• Generate prioritised work-order packages for each cluster and identify critical, urgent, routine and deferrable activities.
• Record and explain any manual changes made to model-generated priorities and rebalance the programme as needed.
• Maintain an accurate view of preventive and corrective maintenance backlog and analyse backlog by cluster, asset type, risk and impact.
• Facilitate backlog reviews with Cluster Leads and escalate high-risk or long-outstanding work to Head of Asset Operations.
• Model resources and time to recover backlog.

Skills

Maintenance planning

Data analytics

Risk assessment

Stakeholder coordination

Education

Bachelor’s degree in Engineering, Data Analytics or related

Tools

CMMS

Asset management systems

Job description

EDP APAC, headquartered in Singapore, seeks a Maintenance Programme Analyst to independently develop and control the solar asset portfolio's maintenance programme. You will convert preventive and corrective maintenance needs into optimised work-orders for execution by clusters.

You will govern maintenance backlog, validate completion data and apply analytics and AI-assisted models to improve prioritisation, resource planning and maintenance performance.