Senior Engineer, Risk Analytics Solutions

Liberty is currently seeking a highly skilled Senior Engineer to join their Risk Analytics Solutions team in Johannesburg. This role serves as a vital link between the complex world of advanced data science and the practical requirements of the organisation’s daily operations. If you enjoy solving architectural puzzles and ensuring that high-level data models function seamlessly in a real-world environment, this position offers a significant opportunity to influence the financial service provider's risk landscape.

About the role

In this position, you will be embedded within a dynamic, cross-functional squad. Your primary focus will be the operationalisation of AI, risk models, and sophisticated strategies. Rather than simply building models, you will be the engineer who ensures that everything from credit scorecards to real-time fraud detection systems is deployed effectively. You will be responsible for building and managing the orchestration solutions within AWS, working specifically with SAS Viya and various AWS services to ensure that the organisation’s risk intelligence remains scalable, robust, and fully automated.

Your daily responsibilities will revolve around bridging the gap between analytical theory and operational stability. You will be expected to:

• Lead the deployment and monitoring of risk-based analytical solutions.
• Develop and maintain automated orchestration pipelines to support risk management services.
• Ensure that all analytical outputs are integrated into a scalable production environment.
• Implement and maintain containerisation and distributed computing solutions.
• Utilise Infrastructure as Code (IaC) principles to manage cloud resources efficiently.
• Collaborate closely with data scientists, risk analysts, and other stakeholders to streamline IT-related processes.

What they're looking for

Liberty is looking for a professional who combines deep technical expertise with strong behavioural competencies. The ideal candidate will be adept at documenting facts, developing technical expertise, and articulating complex information to diverse teams.

**Technical Requirements:**

• A Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related quantitative field.
• 3–5 years of relevant experience, specifically in DevOps, MLOps, Cloud Engineering, or Data Engineering with a heavy emphasis on automation.
• Advanced proficiency in Python programming.
• Demonstrable experience with CI/CD tools such as GitLab Actions, Jenkins, or Azure DevOps.
• Hands-on experience with cloud platforms (AWS is preferred).
• Solid understanding of containerisation technologies like Docker and Kubernetes.
• Experience with Infrastructure as Code (IaC) tools such as Terraform or CloudFormation.
• Familiarity with Big Data frameworks, data integrity, and data quality standards.

For applicants looking to advance their careers in the South African financial sector, roles of this nature typically sit within the senior band of engineering compensation. Senior-level MLOps or Data Engineers at major financial institutions often benefit from competitive benefits packages, including medical aid and pension contributions. This position is ideal for those who have spent several years in cloud or data engineering and are now looking to pivot into the high-stakes, high-impact domain of financial risk management, where growth paths often lead to lead architecture roles or specialised management positions within the broader Standard Bank Group ecosystem.

• Completed Matric
• Bachelor’s degree in computer science, Software Engineering, Information Systems, or a related quantitative field.

Experience

• 3-5 years' experience in the relevant technical role such as DevOps Engineer, MLOps Engineer, Cloud Engineer or Data Engineer with focus on automation.
• Strong programming proficiency, particularly in Python.
• Proven experience with CI/CD tools (e.g. GitLab actions, Azure DevOps, Jenkins)
• Hands-on experience with cloud platforms (AWS or Azure)
• Experience with containerisation technologies and distributed computing (Docker, Kubernetes)
• Familiarity with Infrastructure as Code (IaC) tools (Terraform, Cloud Formation)
   

Behavioural Competencies:

• Adopting Practical Approaches
• Articulating Information
• Developing Expertise
• Documenting Facts
• Embracing Change

Technical Competencies:

• Big Data Frameworks and Tools
• Data Engineering
• Data Integrity
• Data Quality
• IT Knowledge
• Stakeholder Management (IT)