Director: Data Engineering at National Treasury

Qualification/s Requirements

• A Grade 12 is required with a minimum of Bachelor’s degree (equivalent to NQF Level 7) in Computer Science or Software Engineering or Data Science;
• NQF level 8 will be an added advantage;
• A minimum of 5 years’ experience at a middle/senior managerial level obtained in a data and software engineering environment;
• Experience with data integration and modern data warehousing; 
• Knowledge and experience of data governance and security;
• In-depth knowledge in programming languages and software such as R, Python, SQL, AWS; and 
• Successful completion of the Nyukela Public Service Senior Management Leadership Programme as endorsed by the National School of Government available as an online course on https://www.thensg.gov.za/training-course/sms-pre-entry-programme/, prior to finalisation of an appointment.

Key Performance Areas

Data infrastructure and architecture:

• Lead the design, development, and maintenance of data architecture, pipelines, and integrations to ensure seamless data flow and accessibility for advanced analytics;
• Drive innovation in data infrastructure by implementing automation, real-time data processing, and cloud-based solutions;
• Oversee the integration of data sources, data warehousing, and cloud solutions that enable scalable and efficient data processing; and
• Develop interoperable data infrastructure that supports seamless data collection, processing, and analysis within government Digital Public Infrastructure (DPI) systems. 

Data integration, interoperability and automation:

• Oversee data integration to ensure seamless data flow across different systems, platforms, and departments (internal and external); 
• Implement ETL (Extract, Transform, Load) processes to integrate data from various sources;
• Ensure data interoperability to support data sharing and collaboration across divisions within National Treasury;
• Lead the design, development, and implementation of robust, scalable APIs to enable seamless data integration across internal systems and third-party applications; and
• Automate data workflows/processes to streamline data movement and reduce manual processing. 

Data security:

• Implement data security measures, including encryption, data masking, and access controls, to protect sensitive data. Ensure compliance with data protection regulations (e.g. POPIA) and internal security policies; 
• Conduct regular security audits and vulnerability assessments to identify and mitigate risks; and 
• Collaborate with data governance team to establish data quality frameworks, ensuring data accuracy, consistency, and integrity across all systems. 

Stakeholder engagement:

• Engage internal and external stakeholders on new developments pertaining to data architecture;
• Represent National Treasury on inter-governmental and other external forums and committees related to data analytics; and
• Establish relationships with key government departments, research and international organisations to advance data governance functions.