Business Intelligence Analyst

The BI & Reporting Analyst will be part of the Data Science & Analytics team, supporting departments across the business by transforming raw data into meaningful insights. You will play a hands-on role in building SQL data models, designing user-friendly dashboards in Power BI, and automating data workflows to ensure timely, accurate, and actionable reporting.
This position is based at our Bryanston office and reports to the Head of Data Science & Analytics.

Qualifications & Technical Skills

• A Bachelors Degree in Mathematics, Statistics, Computer Science, Engineering, Biology, or equivalent experience
• Strong SQL skills including data modelling, query optimisation, and advanced joins/window functions
• Power BI expertise from semantic model design to interactive dashboard creation (Desktop & Service)
• Python proficiency especially using pandas for data manipulation and SQL integration
• Comfortable with Git (GitHub, GitLab, or Azure Repos) and basic command-line tools
• Experience working across Windows and Linux environments

Key Responsibilities
Business Intelligence & Analytics

• Design clear and intuitive Power BI dashboards for teams across sales, operations, and executive leadership.
• Develop reusable data models and DAX measures to enable self-service insights and scalable reporting.
• Translate business questions into data-driven visual stories that support better decision-making.

Data Engineering & SQL

• Write clean, efficient SQL queries to extract and prepare data from multiple sources.
• Optimise stored procedures, views, and data transformations for clarity and performance.
• Build and maintain lightweight, reproducible data pipelines using Python and/or Databricks.

Automation & Workflow Optimisation

• Develop scripts to automate ETL, reporting refreshes, or data quality checks using Python (pandas, SQLAlchemy, or PySpark).
• Use Git for version control and deploy code using basic CI/CD pipelines when needed.

Documentation & Quality Assurance

• Document dashboards, datasets, and SQL logic for transparency and maintainability.
• Write tests to validate critical SQL queries or Python code and reduce the risk of data errors.

Collaboration

• Work closely with senior data scientists, analysts, and business owners to clarify requirements and deliver value quickly.
• Proactively identify and raise data quality issues and suggest practical solutions rather than short-term fixes.