Requisition ID:13441
CityC. Supply Chian
Group overview:
Headquartered in Riyadh, Saudi Arabia, we operate construction and manufacturing businesses, design & development centers and a host of facilities in the Middle East and other countries.
alfanar is involved in:
- Electrical, Electromechanical and Civil Engineering Construction
- Manufacturing and Marketing Electrical Construction Products
- Allied Engineering Services
Our Main Divisions:
- alfanar electric
- alfanar Construction
- alfanar Building Systems
alfanar electric
alfanar electric is the industrial arm of alfanar, manufacturing a variety of low, medium and high voltage electrical construction products.
alfanar electric operates industries in:
- Riyadh and Jubail, Saudi Arabia
- Dubai, UAE
- London, UK
alfanar has a development and engineering center in Chennai, India.
Industrial Complex, Riyadh
The center of alfanar’s industrial activities is alfanar Industrial Complex situated in the Third Industrial Zone on Al-Kharj Road, Riyadh.
Spread across 700,000 square meters, the Complex houses alfanar’s facilities.
The Complex has a comprehensive infrastructure including a data and communication center as well as a commercial zone.
Job Purpose
Ensuring the accuracy, consistency, and integrity of material master data within the supply chain involves overseeing precise data entry and ongoing maintenance. This includes establishing and enforcing data governance policies, collaborating with various departments to define and maintain data standards, and implementing best practices for supply chain data management. Key tasks involve optimizing data quality through regular validation and issue resolution, enhancing decision-making processes with accurate and actionable insights, and supporting overall business objectives by aligning data practices with organizational goals and continuously improving processes to adapt to evolving supply chain needs.
Key Accountability Areas
Data Governance Strategy:
- Develop and implement a comprehensive data governance strategy specifically for supply chain master data, ensuring alignment with organizational objectives. Define policies, standards, and procedures for the creation, maintenance, and utilization of supply chain master data to enhance operational efficiency.
Stakeholder Collaboration:
- Collaborate with cross-functional teams, including supply chain, IT, finance, and operations, to understand supply chain master data requirements and its usage across different business units. Foster communication and raise awareness about the significance of data governance in optimizing supply chain processes.
Data Quality Management:
- Establish and enforce data quality standards and procedures tailored to supply chain master data to ensure its accuracy and reliability. Implement robust data quality monitoring and remediation processes to address and rectify data discrepancies promptly.
Master Data Standards:
- Define and maintain standards for supply chain master data, including naming conventions, data formats, and classifications. Ensure that these standards comply with industry norms and regulatory requirements to maintain consistency and accuracy.
Master Data Lifecycle Management:
- Develop and implement processes for managing the entire lifecycle of supply chain master data, from creation and modification to archiving and retirement. Apply data governance principles consistently throughout the data lifecycle to support seamless supply chain operations.
Technology Integration:
- Work with IT teams to implement and integrate master data management (MDM) tools and technologies that support supply chain data. Ensure that these tools are effectively integrated with existing systems and applications to maintain data consistency across the supply chain.
Compliance and Security:
- Ensure that supply chain master data governance practices adhere to relevant data protection regulations and security standards. Implement measures to protect sensitive supply chain data from unauthorized access and potential breaches.
Continuous Improvement:
- Regularly assess and enhance supply chain master data governance processes based on feedback, industry best practices, and evolving business needs. Identify opportunities for automation and efficiency improvements to streamline data management practices.
Reporting and Metrics:
- Establish key performance indicators (KPIs) and metrics to evaluate the effectiveness of supply chain master data governance efforts. Generate and analyze reports to track data quality and compliance, providing insights for continuous improvement and strategic decision-making.
Role Accountability
HR Proficiency:
- Training of sub-ordinates and forming a team to get the work effectively.
- Provide leadership, coaching, and direction to subordinates in all aspects of their work.
- Delegate sub-ordinates in each respective assignment.
- Ensures fair distribution of tasks to maintain morale, motivation of subordinates.
Delivery:
- Perform the planned activities to meet the operational and development targets as per delivery schedules.
- Utilize resources effectively to achieve objectives within efficient cost and time.
- Provide a periodic report formatted by detailing the deviation and execution of planned tasks.
Problem-Solving:
- Resolve any related problems arise and escalate any complex operational issues.
Quality:
- Ensure quality requirements to develop effective quality control and processes including specifications for products or processes or related activities.
Business Process Improvements:
- Coordinate well-defined written systems, policies, procedures, and seeking automations opportunities as much as possible.
Compliance:
- Comply to related policy and procedures and work instructions.
Safety:
- Ensure compliance of relevant safety, quality, and environmental management procedures and controls within defined area of work activity to guarantee safety, legislative compliance, and delivery of high-quality products/services.
Academic Qualification
Bachelor Degree in Computer Science or Industrial Engineering
Work Experience
6 to 10 Years
Technical / Functional Competencies
Risk Assessment
Well Organized
Big Data Analytics
Data Cleansing
Data Mining
