Data Analyst

Location: Centurion, Gauteng (provisional – to be confirmed)

Positions Available: 5

Salary: Market-related

Employment Type: To be confirmed

Job Overview We are seeking experienced, analytical and technically proficient Data Analysts to support enterprise data analysis, business intelligence, reporting, data quality management and data-driven decision-making within complex organisational environments.

The successful candidates will be responsible for collecting, extracting, transforming, analysing and interpreting large volumes of structured and semi-structured data to identify trends, evaluate business performance and deliver meaningful insights to business and technical stakeholders.

This role requires strong hands-on expertise in SQL, data analysis, data visualisation, business intelligence tools, statistical analysis and data quality assessment .

The ideal candidates will have proven experience working with enterprise databases, developing analytical reports and dashboards, investigating data discrepancies, identifying business trends and translating complex datasets into clear, actionable recommendations.

Candidates should demonstrate the ability to work independently with data from multiple systems, develop reliable reporting solutions, collaborate with data engineering and business intelligence teams, and communicate analytical findings to stakeholders at different organisational levels.

The role also requires an understanding of data governance, information security, data privacy and enterprise data management principles.

This is a specialist Data Analyst opportunity requiring demonstrated hands-on technical data analysis experience. General administrative reporting, basic Excel usage or data capturing experience alone will not be sufficient. Key Responsibilities

Data Collection, Extraction and Preparation

• Extract data from enterprise databases, applications and information systems.
• Develop and execute SQL queries to retrieve relevant business and operational data.
• Collect and consolidate data from multiple internal and external sources.
• Analyse source data structures and identify relevant datasets.
• Perform data cleansing, transformation and standardisation activities.
• Identify missing, duplicate, inconsistent or inaccurate data.
• Prepare structured datasets for reporting and analysis.
• Validate extracted data against source systems.
• Support the integration of data from different business applications.
• Maintain accurate documentation of data sources, extraction methods and transformation rules.

Data Analysis and Interpretation

• Analyse large and complex datasets to identify trends, patterns and relationships.
• Perform descriptive, diagnostic and exploratory data analysis.
• Investigate business performance trends and operational variances.
• Identify anomalies, outliers and unexpected data behaviour.
• Conduct comparative and historical data analysis.
• Develop analytical models to support business decision-making.
• Interpret analytical results and explain their business implications.
• Identify opportunities for operational efficiency and performance improvement.
• Conduct root cause analysis of data-related business issues.
• Translate analytical findings into practical recommendations.

SQL Development and Database Analysis

• Develop complex SQL queries for data extraction and analysis.
• Use joins, aggregations, subqueries and Common Table Expressions (CTEs).
• Apply window functions and analytical SQL techniques.
• Analyse relational database structures and relationships.
• Develop reusable queries and analytical datasets.
• Investigate data discrepancies across databases and systems.
• Support query optimisation and performance improvement.
• Work with database administrators and data engineers to resolve data issues.
• Validate data accuracy and consistency across reporting environments.
• Document SQL logic and data transformation requirements.

Business Intelligence and Data Visualisation

• Develop interactive dashboards and business intelligence reports.
• Translate business requirements into effective data visualisations.
• Build reports using Power BI, Tableau or equivalent enterprise BI platforms.
• Define and calculate business performance measures.
• Create dashboards to monitor operational and strategic KPIs.
• Develop drill-down reports and interactive analytical views.
• Ensure reports are accurate, understandable and fit for purpose.
• Maintain existing dashboards and reporting solutions.
• Improve report usability, performance and consistency.
• Present data insights using appropriate visualisation techniques.

Power BI and Reporting Development

• Develop and maintain Power BI reports and dashboards.
• Connect Power BI to enterprise databases and approved data sources.
• Prepare and transform data using Power Query.
• Develop data models and relationships to support reporting.
• Create calculated measures and business metrics using DAX.
• Implement appropriate report filters, slicers and navigation.
• Validate Power BI calculations against source data.
• Support scheduled refreshes and reporting reliability.
• Apply appropriate report-level and dataset security controls.
• Optimise report performance and user experience.

Data Quality and Validation

• Conduct data profiling and quality assessments.
• Identify data completeness, consistency, validity and accuracy issues.
• Investigate discrepancies between source systems and reporting outputs.
• Develop data validation and reconciliation procedures.
• Support the implementation of data quality rules and controls.
• Monitor recurring data quality problems.
• Collaborate with data owners and technical teams to resolve issues.
• Document data quality findings and corrective actions.
• Support data quality improvement initiatives.
• Ensure analytical outputs are based on reliable and appropriately validated information.

Statistical Analysis and Analytical Techniques

• Apply appropriate statistical methods to analyse business datasets.
• Conduct trend, variance and correlation analysis.
• Use descriptive statistics to summarise data.
• Support forecasting and predictive analysis where required.
• Perform segmentation and comparative analysis.
• Identify statistically meaningful patterns and anomalies.
• Evaluate analytical assumptions and limitations.
• Use Python, R or equivalent analytical tools where applicable.
• Interpret statistical findings in a business context.
• Communicate analytical conclusions clearly and accurately.

Business Requirements And Stakeholder Engagement

• Engage with business stakeholders to understand analytical and reporting requirements.
• Translate business questions into structured data analysis activities.
• Facilitate discussions regarding KPIs, reporting definitions and data requirements.
• Clarify business rules affecting analytical calculations.
• Present findings to operational managers and senior stakeholders.
• Explain technical analysis in clear business language.
• Collaborate with business analysts, process specialists and business intelligence teams.
• Manage competing reporting and analytical priorities.
• Support data-driven business planning and performance reviews.
• Recommend improvements to reporting and analytical processes.

Enterprise Data Integration and Data Warehousing

• Work with data engineers and database specialists to understand enterprise data structures.
• Analyse data sourced from data warehouses, data marts and operational systems.
• Support data mapping and transformation requirements.
• Understand ETL and ELT processes and their impact on analytical outputs.
• Validate datasets produced by data integration pipelines.
• Identify data lineage and source-to-target relationships.
• Support