A leading organisation is looking to bring on board an experienced Data Analyst to oversee the integration and organisation of data from 19 distinct sources across multiple software platforms and applications. The role involves data cleaning, enhancement, and preparation within a centralised database. Additionally, the analyst will develop automated data processes and create interactive dashboards to drive informed decision-making. The position involves close collaboration with stakeholders and the data team in France, ensuring that data-driven insights align with the organisation's strategic objectives.

If you are interested in applying for this job, please make sure you meet the following requirements as listed below.

Key Responsibilities:

• Oversee the integration and consolidation of data from various software systems and applications across 19 sites in 8 countries.
• Clean, enrich, and prepare data in a centralised database using Python and SQL.
• Create and maintain automated data pipelines to ensure consistent and high-quality data.
• Conduct data analysis to identify insights and trends that support business decision-making.
• Develop interactive dashboards and reports using tools such as Power BI or similar business intelligence platforms.
• Collaborate with stakeholders to understand their data needs and provide tailored solutions.
• Offer data-driven recommendations that support the organisation's strategic growth.
• Work closely with the data team in France and other regions to standardise data practices and share insights.

Qualifications:

• 3-5 years of experience in a data analysis or data science role.
• Strong skills in Python and SQL for data manipulation and analysis.
• Experience with business intelligence tools like Power BI, Tableau, or QlikView.
• Excellent problem-solving and analytical skills.
• Strong communication abilities and experience working with stakeholders.
• Understanding of data engineering concepts and experience with data modelling.
• Familiarity with data visualisation best practices.
• Experience with cloud-based data platforms (e.g., AWS, Microsoft Azure, Google Cloud).