Company Description
Standard Bank Group is a leading Africa-focused financial services group, and an innovative player on the global stage, that offers a variety of career-enhancing opportunities – plus the chance to work alongside some of the sector’s most talented, motivated professionals. Our clients range from individuals, to businesses of all sizes, high net worth families and large multinational corporates and institutions. We’re passionate about creating growth in Africa. Bringing true, meaningful value to our clients and the communities we serve and creating a real sense of purpose for you.
Job Description
The ideal candidate for this role will be responsible for designing and implementing scalable and efficient data solutions using modern data architectures. This includes developing and managing robust ETL/ELT processes and data pipelines to handle a variety of data sources and transformations. A core part of this role is to ensure the quality, integrity, and security of data across all platforms. The candidate will also support hybrid cloud deployments, seamlessly integrating both on-premises and cloud-based environments both on Azure and AWS.
In this position, the individual will collaborate closely with stakeholders to understand business requirements and provide effective technical solutions. They will also be responsible for optimizing data workflows and troubleshooting performance issues. All work must adhere to engineering best practices, including version control and modular code design, to ensure a well-documented and maintainable codebase.
Qualifications
Type of Qualification: First Degree
Field of Study: BSc Computer Science or Information Technology as well as Certifications in Azure or AWS
Experience Required:
- Minimum 4 years’ experience in Data or Software Engineering with strong hands-on experience in Azure or AWS
- Advanced Proficiency in SQL and Python
- Solid understanding of data modelling, data governance, and data warehousing
- Experience with CI/CD pipelines or DevOps (IaaC)
- Experience in MLOps and DataOps is a plus
- Experience in building Data APIs
Additional Information
Behavioural Competencies:
- Adopting Practical Approaches
- Articulating Information
- Challenging Ideas
- Examining Information
- Conveying Self-Confidence
- Convincing People
- Embracing Change
- Exploring Possibilities
- Producing Output
- Pursuing Goals
- Showing Composure
- Upholding Standards
Technical Competencies:
- Big Data Frameworks and Tools
- Data Engineering
- Data Integrity
- IT Knowledge
- Stakeholder Management (IT)
