وظيفة رئيس قسم الرقمنة للأصول لدى شركة المياه الوطنية في السعودية

1. Digital Transformation Leadership

• Lead the digital transformation of asset management functions in alignment with NWC’s Digital Strategy. 
• Drive the adoption of a data-driven and predictive operating model across all CBUs. 
• Promote innovation and continuous improvement in digital asset management practices. 

2. Platforms & Systems Integration

• Oversee the deployment, integration, and optimization of core digital platforms, including: 
  • Geographic Information Systems (GIS) 
  • Enterprise Asset Management Systems (EAMS) 
  • Work Force Management (WFM) systems 
  • Hayat System 
  • IoT platforms 
• Ensure interoperability, scalability, and seamless data flow between systems. 

3. Asset Visibility & Performance Optimization

• Enable centralized visibility and monitoring of assets across geographically distributed networks. 
• Improve asset uptime, reliability, and operational efficiency. 
• Enhance capital investment planning through accurate data insights and forecasting. 
• Develop and monitor asset performance KPIs such as asset availability, reliability, failure rates, and maintenance efficiency. 
• Establish and maintain asset performance dashboards for real-time monitoring at CBU and corporate levels. 
• Support risk-based asset management by linking asset condition, criticality, and performance data. 
• Drive continuous improvement initiatives to enhance asset efficiency and service reliability. 

4. Data Governance & Compliance

• Ensure full adherence to NWC Data Governance Framework. 
• Enforce standards related to: 
  • Data quality and accuracy 
  • Data standardization 
  • Cybersecurity policies 
  • Data access control and privacy 
• Maintain the integrity, reliability, and security of critical asset data. 

5. Advanced Analytics & Automation

• Drive automation of asset management workflows to reduce manual processes. 
• Enable real-time asset condition monitoring using IoT and smart technologies. 
• Lead the implementation of advanced analytics, including AI/ML applications, to support: 
  • Predictive maintenance 
  • Failure forecasting 
  • Lifecycle optimization