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Role purpose

Build and lead a Business Intelligence team that turns business and customer data into practical insights. The role will support business planning, performance improvement, and customer understanding through analysis, research, forecasting, and scenario modelling.

This is a hands-on role requiring strong technical skills and the ability to explain findings clearly to business stakeholders.

Key responsibilities

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Analyse business performance and customer behavior to identify trends, opportunities, and areas for improvement.

• Develop dashboards and automate reports to support management decisions.

• Combine data from Microsoft Dynamics 365, retail systems, and Loyalty & Rewards platforms into reliable datasets.

• Build forecasts and scenario models to evaluate business initiatives and potential outcomes.

• Conduct research and assess the effectiveness of promotions, customer programmes, and other initiatives.

• Work with business teams to understand their needs and translate them into analytical solutions.

• Maintain data accuracy, consistent reporting definitions, documentation, and appropriate access controls.

• Present findings and recommendations clearly to management.

• Build, manage, and develop the BI team, prioritizing work according to business needs.

• Collaborate with IT and system partners to improve data availability and reporting processes.

Qualifications and experience

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Bachelor’s degree in Data Science, Statistics, Computer Science, Information Systems, Economics, or a related field, or equivalent practical experience.

• At least 5 years of relevant experience in business intelligence or data analytics, including experience leading projects or supervising analysts.

• Experience turning complex data into practical business recommendations.

• Strong problem-solving, communication, and stakeholder management skills.

• Experience in retail, consumer businesses, or loyalty programmes is preferred.


Required technical skills

• SQL: Strong ability to extract, combine, and analyse large datasets.
• Power BI: Experience building data models, dashboards, and automated reports using DAX and Power Query.
• Python or R: Practical experience in data preparation, statistical analysis, and forecasting.
• Excel: Advanced analytical and modelling skills.
• Data integration: Understanding of data pipelines, database structures, and data-quality checks.
• Analytical methods: Experience with customer segmentation, forecasting, scenario modelling, and evaluating business initiatives.