Data Analyst at Capitec Bank

• At Capitec, we're building a more insights-driven card business by making trusted, meaningful data accessible to decision-makers across the organisation.  As a Data Analyst within the Client Card Insights team, you will play a key role in transforming card, client, merchant and product data into actionable insights that influence strategic decision-making. You will work closely with business owners, product teams, portfolio managers and operational stakeholders to understand challenges, identify opportunities and deliver data solutions that improve client outcomes and business performance. This role goes beyond report development. You'll help drive the evolution of our analytics landscape by contributing to self-service reporting capabilities, reporting modernisation initiatives and advanced analytical solutions. If you enjoy solving complex business problems, working with large-scale datasets and turning data into compelling stories that influence decisions, we'd love to hear from you.

What you'll be doing

• Deliver meaningful insights across Capitec's card and payment ecosystem, helping stakeholders understand client behaviour, product performance and operational trends.
• Partner with business stakeholders to translate business questions into analytical solutions and measurable outcomes.
• Develop and maintain dashboards, analytical datasets and reporting solutions using Power BI and enterprise data platforms.
• Analyse large, complex datasets to identify trends, opportunities, risks and performance drivers.
• Support strategic initiatives through data-driven recommendations and impact analysis.
• Contribute to the design and adoption of self-service analytics capabilities that empower business users to access and explore trusted data independently.
• Work with modern data platforms and semantic models to improve data accessibility, consistency and governance.
• Perform root-cause investigations and diagnostic analysis to support business decision-making.
• Present findings and recommendations to both technical and non-technical audiences.
• Collaborate with data engineering, product, operational and analytics teams to improve data quality and reporting capabilities.
• Drive continuous improvement through automation, standardisation and innovative uses of data and AI-enabled analytics. 

What we're looking for

• You are passionate about using data to solve business problems and have a strong balance of technical expertise, stakeholder engagement and business understanding. 

You should be comfortable: 

• Working directly with business stakeholders and product owners.
• Navigating complex data environments and multiple data sources.
• Translating technical insights into business-friendly recommendations.
• Managing analytical initiatives from requirement gathering through to delivery.
• Challenging assumptions and using data to influence decision-making.
• Identifying opportunities to improve processes through automation and standardisation. 

Preferred experience

• Banking, payments, cards or financial services analytics.
• Customer, product or portfolio analytics.
• Merchant and transaction analysis.
• Client behaviour and engagement analytics.
• Performance measurement and KPI design.
• Self-service analytics enablement.
• Reporting migration and modernisation initiatives.
• Data quality, governance and business rule implementation. 

Technical skills
We are looking for strong capability in: 

• Advanced SQL: Complex querying, performance optimisation and large-scale data analysis.
• Power BI: Report development, dashboard design and effective data visualisation.
• Data modelling: Dimensional and semantic model concepts that make data easier to use.
• Analytical methods: Statistical analysis, trend identification and diagnostic investigation.
• Data storytelling: Clear communication of findings, implications and recommendations.
• Solution design: Performance optimisation and practical analytical solution design. 

What success looks like

• Deliver insights that drive measurable business outcomes.
• Enable stakeholders to make faster and better decisions through trusted data.
• Improve the accessibility and usability of analytics across the organisation.
• Contribute to the evolution of self-service reporting capabilities.
• Identify opportunities for automation and operational efficiency.
• Become a trusted analytics partner to business stakeholders. 

Minimum Experience

• A minimum of 5 years' experience as a Data Analyst.
• Experience in data analysis across one or more industries, with a proven ability to generate insights and support data-driven decision-making.
• Proven track record of leading data analysis projects and driving business impact through data insights.
• Experience using advanced data analysis tools and software (e.g. SQL, Python, R, Tableau, Power BI).
• Experience performing complex data analysis and statistical modelling.
• Experience working with, guiding, and providing subject matter expertise to cross-functional teams (e.g. Finance, Marketing, IT) to understand business needs and provide data-driven insights.
• Experience communicating and presenting findings and recommendations to non-technical stakeholders.
• Understanding of industry trends, regulations, compliance requirements, and their impact on data analysis.
• Familiarity with financial products and services would be advantageous.

Qualifications (Minimum)

• Bachelor's Degree in Analytical/Data/Technical or Other

Knowledge

• Advanced proficiency in writing complex SQL queries, optimizing query performance, and working with large datasets.
• Expertise in advanced Excel functions, including macros and VBA.
• Proficiency in creating advanced visualizations and dashboards using tools like Tableau, Power BI, or similar.
• Advanced skills in Python or R, including data manipulation libraries (e.g., pandas, numpy) and data visualization libraries (e.g., matplotlib, seaborn).
• Strong understanding of statistical methods and their application in financial data analysis.
• Understanding of predictive analytics techniques and their application in financial analysis.
• Knowledge of data modelling techniques to structure and organize data effectively.
• Understanding of risk analysis methods and their application in financial services.

Conditions of Employment

• Clear criminal and credit record