Personal and Private Banking (PPB) Data Engineer Graduate Programme at Standard Bank Group

What You'll Learn & Contribute To

Data Fundamentals

• Assist in building data pipelines that transform raw data into useful information
• Learn to work with different types of databases and data models
• Help with data migration projects between systems
• Gain hands-on experience analyzing data quality and suggesting improvements
• Collaborate with team members to understand how data flows across systems

Technology & Tools

• Develop skills working with industry-standard data technologies and cloud platforms
• Learn about data infrastructure and how to optimize it for performance
• Get introduced to API concepts and how they enable data sharing
• Build foundational knowledge in programming languages used for data processing
• Experience how automation can improve data workflows

Collaboration & Communication

• Work alongside experienced data professionals who will mentor your development
• Participate in meetings with business teams to understand their data needs
• Learn how to translate technical concepts into business-friendly language
• Contribute ideas and perspectives as part of a diverse team

Innovation & Growth

• Help identify opportunities to improve existing processes
• Learn to create tools that make data more accessible to other teams
• Apply your academic knowledge to real-world business problems
• Develop both technical and business understanding of data's value

Best Practices & Governance

• Learn about data security, privacy, and compliance requirements
• Understand how data quality is maintained throughout its lifecycle
• Gain exposure to industry standards and best practices
• See how proper documentation ensures data usability and traceability

Qualifications

Final year undergraduate, Honours or Masters Degree (Completed or currently completing in 2025) in:

• Computer Science
• Artificial Intelligence and Machine Learning
• Electronic Engineering
• Mechatronic Engineering
• Mechanical Engineering
• Mathematics, Applied Mathematics
• Informatics, Information Systems
• Software Development
• Software Engineering
• Data Engineering
• Data Science
• Quantitative Risk Management