Capitec Bank is looking for a passionate and experienced Data Architect to join our dynamic team. If you're excited by data, cloud technology, and making a real impact on millions of lives, this is your chance to help build the bank of the future.

We're on a journey to simplify banking and improve client experiences through smart, scalable, and secure data systems. Join us and be part of something meaningful!

The Role

As the Lead Data Architect at Capitec Business Bank, you will be responsible for designing modern, scalable data solutions that support decision-making, artificial intelligence (AI), and client service innovation.

You will create the roadmap for our data architecture, lead technical standards, and mentor teams across the business. If you're a problem-solver who can turn complex ideas into simple, effective systems – we want you on our team.

Key Responsibilities

• Develop and maintain the enterprise data strategy (e.g. data mesh, data fabric).

• Define standards and best practices for data design and architecture.

• Design complete data solutions – from data lakes and warehouses to real-time analytics and AI features.

• Build cloud-native or hybrid platforms, preferably on AWS.

• Create and manage data models (conceptual, logical, physical).

• Collaborate with teams like AI, product, risk, and engineering.

• Mentor junior data professionals and contribute to leadership forums.

• Ensure compliance with POPIA, GDPR, and other data regulations.

• Evaluate and recommend new data tools, frameworks, and technologies.

Requirements

Education & Certifications:

• Bachelor’s or Master’s in Computer Science, Information Systems, Engineering, or similar.

• Cloud certifications (e.g., AWS Data Analytics, Data Engineer, Solutions Architect).

• Data architecture certifications (e.g., DAMA CDMP, TOGAF) – Advantageous.

Experience:
Minimum 7 years in data architecture, including:

• Designing and evolving enterprise-level data strategies.

• Building data solutions across different environments (cloud, hybrid).

• Working with AI/ML models and their supporting data pipelines.

• Implementing data governance, security, and regulatory compliance.

• Leading teams and working with cross-functional departments.

Knowledge:

Must-Have:

• Data warehouse development lifecycle

• Dimensional data modeling

• Understanding of financial systems

• UML or other modeling tools

• Experience with AI/ML feature stores

• Software development and testing processes

• Strong grasp of IT standards and governance

Nice-to-Have:

• Experience in banking or financial systems

• Agile development knowledge

• Quality assurance best practices