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Job summary

The BI Analytics & Insights Analyst is responsible for transforming raw data into actionable business insights through advanced analytics, data engineering, visualization, and predictive modelling.

The role bridges business intelligence to support strategic decision-making, operational efficiency, and a data-driven culture while ensuring strong data governance and quality standards.

Key responsibilities and approximate time split

Business intelligence and analytics

The Business Intelligence Analyst will be responsible for supporting business teams with analytics, reporting, and insights that improve business performance and decision-making.

Key duties include:

• Partnering with business stakeholders to understand analytical requirements and translate them into BI and advanced analytics solutions.
• Developing, maintaining, and optimizing BI solutions that provide insights into business performance, trends, and risks.
• Defining and managing KPIs, metrics, and analytical frameworks aligned with business strategy.
• Performing deep-dive analyses to identify patterns, root causes, and improvement opportunities.
• Designing and maintaining KPIs covering:
  • Revenue and profitability.
  • Customer acquisition and retention.
  • Credit portfolio performance.
  • Liquidity and balance sheet metrics.
• Supporting management reporting, executive dashboards, and board-level insights.
• Providing root-cause and variance analysis for financial and operational performance.

Data engineering and data modelling

The role also involves building and maintaining strong data foundations to support analytics and reporting.

Key duties include:

• Designing, building, and maintaining scalable data pipelines, including ETL/ELT, from multiple source systems.
• Developing and optimizing data models, including star and snowflake schemas, for analytics and reporting.
• Ensuring data accuracy, consistency, and performance across analytical datasets.
• Collaborating with IT and cloud teams on data architecture and platform optimization.

Power BI and data visualization

The Business Intelligence Analyst will design and deliver effective dashboards and reports that support business users and decision-makers.

Key duties include:

• Designing and delivering interactive, high-performance Power BI dashboards and reports.
• Applying best practices in data visualization, UX/UI, and storytelling.
• Implementing DAX calculations, measures, and time intelligence.
• Managing Power BI datasets, data refreshes, security, Row-Level Security, and deployment pipelines.
• Managing dataset refreshes, performance optimization, and Row-Level Security.

Data governance and data quality

The role requires maintaining strong data governance, documentation, and compliance standards.

Key duties include:

• Enforcing data governance standards, definitions, and master data management.
• Ensuring compliance with data privacy, security, and regulatory requirements.
• Implementing data quality checks, validation rules, and documentation.
• Maintaining data dictionaries, lineage, and metadata.

Stakeholder support and analytics advisory

The analyst will support business users and contribute to the continuous improvement of analytics practices.

Key duties include:

• Acting as a trusted analytics advisor to business teams.
• Training and supporting users on BI tools, dashboards, and data interpretation.
• Contributing to analytics best practices, standards, and continuous improvement initiatives.

Required qualifications

Applicants must have the following qualifications:

• Bachelor’s degree in Computer Science, Actuarial Science, Data Science, Statistics, Information Systems, Engineering, Economics, or a related field.
• A Master’s degree is an added advantage.

Preferred experience

The preferred candidate should have:

• A minimum of 4 years of technical experience.
• Experience working within a large, complex organization with multiple stakeholders.

Knowledge and skills

Technical skills

Applicants should demonstrate strong technical knowledge and hands-on experience in the following areas:

• Business intelligence: KPI design, analytics frameworks, and stakeholder engagement.
• Power BI: Advanced DAX, Power Query, data modelling, Row-Level Security, and performance optimization.
• Data engineering: Advanced SQL, ETL/ELT, data pipelines, and data warehousing.
• Databases: SQL Server, PostgreSQL, Oracle, or cloud data platforms.
• Data governance: Data quality, metadata management, privacy, and security concepts.

Behavioural competencies

The successful candidate should demonstrate the following behavioural competencies:

• Problem-solving skills
  Ability to identify and solve complex problems using analytical thinking and creativity.
• Attention to detail
  Ability to maintain accuracy and thoroughness in all tasks, from data collection to analysis and reporting.
• Curiosity and continuous learning
  Passion for learning and keeping up with the latest trends and developments in the field of data science.
• Strong analytical thinking
  Ability to approach problems in a logical and systematic manner, using data-driven insights to guide decision-making.
• Effective communication skills
  Ability to articulate complex ideas and findings in a clear and concise manner, both verbally and in writing.
• Time management and prioritization
  Ability to manage multiple projects and deadlines, prioritize tasks effectively, and deliver high-quality work on time.
• Adaptability and flexibility
  Ability to adjust to changing priorities, work in a dynamic environment, and thrive in a fast-paced setting.

Absa values

Absa’s values and behaviours represent the set of standards that govern the actions of all employees who work for the bank. These values are also used to assess and reward performance across Absa.

The values include:

• Trust.
• Resourceful.
• Stewardship.
• Inclusive.
• Courage.

• Partnering with business stakeholders to understand analytical requirements and translate them into BI and advanced analytics solutions.
• Developing, maintaining, and optimizing BI solutions that provide insights into business performance, trends, and risks.
• Defining and managing KPIs, metrics, and analytical frameworks aligned with business strategy.
• Performing deep-dive analyses to identify patterns, root causes, and improvement opportunities.
• Designing and maintaining KPIs covering: Revenue and profitability, Customer acquisition and retention, Credit portfolio performance, Liquidity and balance sheet metrics.
• Supporting management reporting, executive dashboards, and board-level insights.
• Providing root-cause and variance analysis for financial and operational performance.
• Designing, building, and maintaining scalable data pipelines, including ETL/ELT, from multiple source systems.
• Developing and optimizing data models, including star and snowflake schemas, for analytics and reporting.
• Ensuring data accuracy, consistency, and performance across analytical datasets.
• Collaborating with IT and cloud teams on data architecture and platform optimization.
• Designing and delivering interactive, high-performance Power BI dashboards and reports.
• Applying best practices in data visualization, UX/UI, and storytelling.
• Implementing DAX calculations, measures, and time intelligence.
• Managing Power BI datasets, data refreshes, security, Row-Level Security, and deployment pipelines.
• Managing dataset refreshes, performance optimization, and Row-Level Security.
• Enforcing data governance standards, definitions, and master data management.
• Ensuring compliance with data privacy, security, and regulatory requirements.
• Implementing data quality checks, validation rules, and documentation.
• Maintaining data dictionaries, lineage, and metadata.
• Acting as a trusted analytics advisor to business teams.
• Training and supporting users on BI tools, dashboards, and data interpretation.
• Contributing to analytics best practices, standards, and continuous improvement initiatives.

• Business intelligence: KPI design, analytics frameworks, and stakeholder engagement.
• Power BI: Advanced DAX, Power Query, data modelling, Row-Level Security, and performance optimization.
• Data engineering: Advanced SQL, ETL/ELT, data pipelines, and data warehousing.
• Databases: SQL Server, PostgreSQL, Oracle, or cloud data platforms.
• Data governance: Data quality, metadata management, privacy, and security concepts.
• Problem-solving skills
• Attention to detail
• Curiosity and continuous learning
• Strong analytical thinking
• Effective communication skills
• Time management and prioritization
• Adaptability and flexibility

• Bachelor’s degree in Computer Science, Actuarial Science, Data Science, Statistics, Information Systems, Engineering, Economics, or a related field.
• A Master’s degree is an added advantage.