Data Engineer at Capitec Bank
Capitec Bank
September 24, 2026
Full-time
On-site
About the role
The role forms part of the Client Engagement Delivery — the team that builds and maintains the data foundation powering our client engagement and campaign activity. We design data assets and pipelines that deliver trusted, accurate data to Salesforce Marketing Cloud and Data360, giving CRM Architects, Specialist Client Engagement teams and Product Owners what they need to run targeted, data-driven campaigns and client journeys.
Our work covers the full data lifecycle — from approved Business Requirements Specifications (BRS) through architecture, development, testing and deployment of production-ready pipelines. We make sure data is reliable and actionable across every channel: in-app, WhatsApp, email, SMS and branch. They partner with Business Analysts, Product Owners and Marketing Managers to translate business decisions into deployable pipelines — and support post-campaign measurement by publishing performance data to the EDW for continuous improvement. If you're a data engineer who wants to see your work reach millions of real clients across real channels, this is where you do it.
What you'll do
Design, build and maintain robust, scalable and efficient data pipelines and systems that meet the needs of our data environment
Analyse business and system requirements to build and enhance data platforms
Provide input to the Data Architect during solution design for new and existing data flows
Contribute to the design and development of new applications and systems
Support and maintain data infrastructure to keep it reliable and efficient
Education (Minimum)
Grade 12 National Certificate / Vocational
Bachelor's Degree in Information Technology - Computer Science or Information Technology
Education (Ideal or Preferred)
Honours Degree in Information Technology - Computer Science or Information Technology
Knowledge and Experience
Knowledge:
Advanced SQL — modelling principles and query optimisation
Hands-on experience with batch processing and basic implementation of stream processing
Proficiency in multiple programming languages — able to build reusable components and optimise code
ETL pipeline design — with error handling and recovery mechanisms
Deep knowledge of at least one cloud platform's data services
Implementation of data lake, data warehouse or other data patterns
Implementation of data quality and governance
Ability to performance-tune data systems and pipelines, balancing cost against performance
Advanced version control and CI/CD principles — including automated testing
Implementation of containerised data solutions
Infrastructure as code — creation and setup of workflow orchestration tools
Minimum Experience:
5 years in Data Engineering or closely related field
Leading or significantly contributing to data engineering projects
Using advanced data engineering tools — SQL, Python, Java, Apache Spark, Hadoop
Cloud platforms — AWS, Google Cloud or Azure — and Big Data technologies
Building and optimising data pipelines for financial data analytics
Working with cross-functional teams to understand business needs and deliver data-driven solutions
Engaging stakeholders — communicating technical details and project progress to non-technical audiences
Understanding of various financial products and services
Awareness of market trends and their impact on data engineering
Skills
Analytical Skills
Communications Skills
Interpersonal & Relationship management Skills
Problem solving skills
Additional Information
Clear criminal and credit record
The role forms part of the Client Engagement Delivery — the team that builds and maintains the data foundation powering our client engagement and campaign activity. We design data assets and pipelines that deliver trusted, accurate data to Salesforce Marketing Cloud and Data360, giving CRM Architects, Specialist Client Engagement teams and Product Owners what they need to run targeted, data-driven campaigns and client journeys.
Our work covers the full data lifecycle — from approved Business Requirements Specifications (BRS) through architecture, development, testing and deployment of production-ready pipelines. We make sure data is reliable and actionable across every channel: in-app, WhatsApp, email, SMS and branch. They partner with Business Analysts, Product Owners and Marketing Managers to translate business decisions into deployable pipelines — and support post-campaign measurement by publishing performance data to the EDW for continuous improvement. If you're a data engineer who wants to see your work reach millions of real clients across real channels, this is where you do it.
What you'll do
Design, build and maintain robust, scalable and efficient data pipelines and systems that meet the needs of our data environment
Analyse business and system requirements to build and enhance data platforms
Provide input to the Data Architect during solution design for new and existing data flows
Contribute to the design and development of new applications and systems
Support and maintain data infrastructure to keep it reliable and efficient
Education (Minimum)
Grade 12 National Certificate / Vocational
Bachelor's Degree in Information Technology - Computer Science or Information Technology
Education (Ideal or Preferred)
Honours Degree in Information Technology - Computer Science or Information Technology
Knowledge and Experience
Knowledge:
Advanced SQL — modelling principles and query optimisation
Hands-on experience with batch processing and basic implementation of stream processing
Proficiency in multiple programming languages — able to build reusable components and optimise code
ETL pipeline design — with error handling and recovery mechanisms
Deep knowledge of at least one cloud platform's data services
Implementation of data lake, data warehouse or other data patterns
Implementation of data quality and governance
Ability to performance-tune data systems and pipelines, balancing cost against performance
Advanced version control and CI/CD principles — including automated testing
Implementation of containerised data solutions
Infrastructure as code — creation and setup of workflow orchestration tools
Minimum Experience:
5 years in Data Engineering or closely related field
Leading or significantly contributing to data engineering projects
Using advanced data engineering tools — SQL, Python, Java, Apache Spark, Hadoop
Cloud platforms — AWS, Google Cloud or Azure — and Big Data technologies
Building and optimising data pipelines for financial data analytics
Working with cross-functional teams to understand business needs and deliver data-driven solutions
Engaging stakeholders — communicating technical details and project progress to non-technical audiences
Understanding of various financial products and services
Awareness of market trends and their impact on data engineering
Skills
Analytical Skills
Communications Skills
Interpersonal & Relationship management Skills
Problem solving skills
Additional Information
Clear criminal and credit record