Head of Data Management at Postbank (SOC) Ltd

Data Strategy Development and Execution

• Develop and implement a comprehensive data management strategy aligned with the bank’s business goals.
• Drive the adoption of best practices for data management across the organization.
• Ensure data assets are managed and utilized effectively to support decision-making.

 Data Architecture and Infrastructure

• Oversee the design, implementation, and maintenance of the bank’s data architecture.
• Collaborate with IT teams to ensure data systems and platforms are scalable, secure, and efficient.
• Evaluate and implement data management technologies and tools.
• Data Quality and Integrity
• Lead efforts to ensure data accuracy, completeness, and reliability across the organization.
• Develop and enforce data quality standards and metrics.
• Implement data cleansing and validation processes.

 Team Leadership and Development

• Build and manage a high-performing data management team, including data governance, data architecture, data scientists and data quality professionals.
• Provide mentorship, training, and career development opportunities to team members.
• Foster a collaborative and innovative team culture.

 Collaboration and Stakeholder Management

• Work closely with business units to understand their data needs and challenges.
• Partner with IT, risk, and compliance teams to ensure data management aligns with broader organizational goals.
• Communicate data management strategies and progress to executive leadership.

 Risk Management

• Identify and mitigate risks related to data management, including data breaches and unauthorized access.
• Ensure data management practices align with the bank’s risk management framework.

 Innovation and Continuous Improvement

• Stay abreast of industry trends and advancements in data management.
• Continuously improve data management practices and processes to enhance efficiency and effectiveness.
• Drive innovation in data usage, including the implementation of advanced analytics and AI-driven insights.

 Data Lifecycle management and Metadata management

• Ensure policies, processes and standards exist for data lifecycle management (i.e. Management of data from creation to deletion) and for metadata management
• Ensure metadata is up-to-date and accessible

 Master Data Management

• Ensure policies, processes and standards exist for master data management
• Drive the centralization of key data (like customer information and product data) and ensure it is consistent across the bank.

 Data Integration

• Ensure that data required to provide BI is combined from different sources to provide a unified view for Analytics team to utilize.
• Focus areas to achieve this include ETL processes, provision of data lakes, APIs and data synchronization between systems. 

 Qualifications, Experience, Knowledge and understanding of:

• Completed a Post B-Degree in Computer Science, Information Systems, Data Management, Engineering or related field (NQF8)
• Completed or studying towards a master’s qualification
• At least 10 years’ experience in implementing and managing a data management function
• + 5 years banking or financial industry experience
• Proven track record of developing and implementing data management strategies and governance frameworks.
• Strong understanding of data management tools and technologies (e.g., SQL, ETL processes, data lakes, cloud platforms).
• Knowledge of regulatory requirements related to data management and privacy.
• Proficiency in data analytics and business intelligence tools.
• Strong understanding and experience with data architecture design, data warehousing, and data integration.
• Understanding of business operations and banking industry