Data Engineer

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

To provide technical leadership in the design, delivery, and continuous evolution of enterprise data architecture, data platforms, and AI engineering capabilities. The role enables the organisation to derive value from data by establishing scalable, secure, and governed data foundations, engineering high-quality data products, and supporting advanced analytics, machine learning, and generative AI use cases. The role ensures that all data solutions are aligned to enterprise architecture standards, governance requirements, security controls, and strategic technology objectives while promoting data reliability, interoperability, and operational excellence.

Qualifications

Type of Qualification: First Degree

Field of Study: Information Technology, Mathematics, Statistics, Business Commerce or a related discipline

Relevant professional certifications in cloud data platforms, data architecture, data engineering, data science, machine learning or AI engineering will be an advantage.

Experience Required

8-10years

• Experience in building databases, warehouses, reporting and data integration solutions.
• Experience building and optimising big data data-pipelines, architectures and data sets.
• Experience in creating and integrating APIs. Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
• Deep understanding of data pipelining and performance optimisation, data principles, how data fits in an organisation, including customers, products and transactional information. Knowledge of integration patterns, styles, protocols and systems theory
• Experience in database programming languages including SQL, PL/SQL, SPARK and or appropriate data tooling.
• Experience with data pipeline and workflow management tools

Behavioural Competencies:

• Articulating Information
• Developing Expertise
• Interpreting Data
• Managing Tasks
• Producing Output
• Team Working

Technical Competencies:

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

• Business Segment: Corporate & Investment Banking