Data Analyst II

Purpose of the role:

The Data Analyst II role exists to unlock value from data by making it accessible, trusted, and meaningful to stakeholders across the organisation. This role transforms complex data into actionable insights that support strategic decision‑making, optimise operations, and improve business performance.
By identifying trends, patterns, and opportunities across multiple data sources—including enterprise platforms such as Salesforce—the role contributes directly to Capitec’s objective of being an insights‑driven organisation.

What you'll do:

• Analyse complex datasets to deliver clear, actionable insights that inform business decisions
• Lead and contribute to end‑to‑end data analysis initiatives with measurable business impact
• Work closely with cross‑functional teams (e.g. finance, marketing, IT) to understand business needs and translate them into data solutions
• Build and maintain high‑quality reports, dashboards, and data models using tools such as SQL, Python, Power BI, Tableau, and Salesforce‑related data sources
• Apply statistical and analytical techniques to uncover trends, risks, and opportunities
• Communicate findings clearly to non‑technical stakeholders, tailoring insights for different audiences
• Ensure data accuracy, consistency, and governance across reporting and analytics outputs

Experience

• Honours degree in an analytics or STEM  or  related field, PLUS at least 5yrs relevant experience  OR
• Bachelor degree in an analytics or STEM  or  related field, PLUS at least 8yrs relevant experience 
  Proven experience in data analysis, with a strong preference for exposure to financial services or banking
• Demonstrated ability to lead data analysis work and drive business outcomes through insights
• Hands‑on experience using advanced analytics tools (e.g. SQL, Python, R, Power BI, Tableau)
• Experience performing complex data analysis and statistical modelling
• Experience working with enterprise platforms and data models; Salesforce data experience is preferred, particularly back‑end data structures rather than front‑end user configuration
• Strong stakeholder engagement experience, including presenting insights to non‑technical audiences
• Understanding of financial products, industry trends, and regulatory or compliance considerations impacting data analysis

Qualifications (Minimum)

Qualifications (Ideal or Preferred)

Knowledge

• Advanced SQL (complex queries, performance optimisation, large datasets)
• Advanced Excel, including macros and VBA
• Data visualisation and dashboarding (Power BI, Tableau, or similar)
• Python or R for data manipulation and visualisation
• Statistical methods and predictive analytics techniques
• Data modelling concepts and best practices
• Risk analysis principles within financial services

Skills

Conditions of Employment