What you will do
- Collect, extract, clean, and transform data from multiple sources to ensure accuracy and reliability.
- Analyse large datasets to identify trends, patterns, business opportunities, and actionable insights.
- Develop, maintain, and enhance interactive dashboards and reports using Power BI, Qlik, and Microsoft Fabric.
- Create effective data visualizations and apply data storytelling techniques to communicate findings to business stakeholders.
- Write complex SQL queries for data extraction, transformation, and analysis, ensuring optimal query performance.
- Perform statistical analysis and exploratory data analysis (EDA) to support evidence-based business decisions.
- Collaborate with business stakeholders to understand reporting requirements, data needs, and key performance indicators (KPIs).
- Establish and maintain reporting schedules, dashboard refresh cadences, and Service Level Agreements (SLAs).
- Implement data quality checks, validation rules, and reconciliation processes to maintain data accuracy and consistency.
- Work closely with Data Engineers on data modelling, including Star and Snowflake schemas.
- Contribute to centralized business definitions, metrics catalogues, and data documentation.
- Document analytical methodologies, reporting processes, data sources, and dashboard update schedules.
- Identify opportunities for process improvement and recommend data-driven solutions.
- Present analytical findings and actionable recommendations to technical and non-technical stakeholders, including senior management.
What you bring
- Experience in data analysis, data manipulation, and reporting using SQL, Python, or R.
- Hands-on experience with data visualization and business intelligence tools such as Power BI, Qlik, or Microsoft Fabric.
- Knowledge of statistical analysis techniques and tools such as SPSS, Python libraries, or R.
- Strong proficiency in Microsoft Excel for data analysis, manipulation, and reporting.
- Understanding of data warehousing concepts, including Star Schema, Snowflake Schema, and dimensional modelling.
- Familiarity with modern data platforms such as Microsoft Fabric, Snowflake, BigQuery, and Azure Synapse.
- Experience with data preparation and transformation tools such as Power Query, Alteryx, or dbt.
- Knowledge of ETL processes and data integration tools such as SSIS, Informatica, Talend, or Azure Data Factory.
- Understanding of cloud-based data services and modern analytics platforms.
- Knowledge of data quality management, validation, reconciliation, and data lineage practices.
- Familiarity with metadata management and data governance tools such as Microsoft Purview and Collibra.
How you work
- Analyse complex datasets, identify meaningful patterns, and translate findings into business insights.
- Communicate analytical results through clear visualizations, dashboards, and compelling data stories.
- Translate business requirements into effective reporting solutions and measurable KPIs.
- Present concise, actionable, and decision-oriented recommendations to senior stakeholders.
- Ensure data accuracy, consistency, and integrity through effective validation and quality control.
- Troubleshoot data discrepancies and recommend appropriate corrective actions.
- Manage multiple analytical tasks and deliver quality outputs within agreed timelines.
- Work independently as well as collaboratively with cross-functional teams.
- Participate effectively in multilingual meetings and communicate fluently in English; knowledge of French is an added advantage.
- Adapt to new technologies, data platforms, analytical methodologies, and business requirements.
- Demonstrate excellent interpersonal, communication, problem-solving, and stakeholder-management skills.
- Maintain a proactive, flexible, and results-oriented approach to delivering business insights.
What you can expect
- An opportunity to work on modern data analytics and business intelligence initiatives.
- Exposure to enterprise-level data platforms, cloud technologies, and reporting solutions.
- Opportunities to collaborate with Data Engineers, business stakeholders, and cross-functional teams.
- A professional environment that encourages continuous learning and technical development.
- Opportunities to contribute to data-driven business decisions and analytics improvements.