The Person

For the above position, the successful applicant should have the following:

• Bachelor’s degree in data science or related fields (Required).
  
• Master’s degree in strategic management / business administration or Related (Added advantage).
  

• Certification in data governance frameworks like DAMA DMBOK, COBIT, or ISO/IEC 38500.SQL, R, Python, Supervised and unsupervised machine learning techniques (added advantage).
  

• 8 years’ work experience with the below;-
  

• 8 years’ progressive experience in data management or analytics(essential).
  
• 8 years’ experience in Data Quality Management(essential).
  
• 4 years’ experience in Data Remediation program(essential).
  
• 4 years’ experience in Data governance frameworks(essential).
  
• 4 years’ experience in SQL, Python/R, and cloud computing(essential).
  
• 6 years’ experience in People management(essential).
  
• 2 years’ experience in Data monetization(desired).
  
• 2 years’ experience in Machine learning, AI(desired).
  
• 2 years’ experience in Project Management(desired).
  

• Define and execute the Group Enterprise Data Strategy and Roadmap, aligned to the Group Strategy and priorities.
  

• Establish and enforce Group-wide Data Governance, including data ownership, stewardship, policies, and decision rights across subsidiaries.
  

• Build the Enterprise Data Operating Model, including federated governance structures and subsidiary-level data leads with dotted-line accountability.
  

• Own the Enterprise Data Architecture, including master data, metadata management, lineage, and reference data standards.
  

• Drive Data Quality and Data Integrity Programs, including enterprise data quality SLAs, remediation, and continuous monitoring.
  

• Lead Data Platform and Analytics Enablement, shaping the target data stack and working with Technology to implement scalable data infrastructure.
  

• Enable AI and Advanced Analytics Adoption, ensuring data readiness, ethical AI governance, model risk controls, and business use-case prioritization.
  

• Drive Business Value Realization and Data Monetization, ensuring measurable revenue uplift, cost savings, productivity gains, and new product opportunities.
  

• Ensure Regulatory Compliance and Data Risk Management, including privacy, cybersecurity controls, retention policies, audit readiness, and BC/DR requirements.
  

• Build Group-wide Data Culture and Capability, including analytics literacy, talent development, and enterprise-wide change management.
  
• Collaborate with the Technology Management team to shape the information technology strategy, in particular pertaining to the data and analytics technology stack, critical workflows and channel infrastructure.