Data Analyst (Global Logistics Project)

About the role

We are seeking a Data Analyst to support a global logistics project, driving data analytics, business intelligence and AI/ML initiatives across multiple markets. The role will work with Microsoft Fabric, Power BI and advanced analytics tools to deliver actionable insights.

Key responsibilities

• Analyze logistics, supply chain, transportation and operational data to uncover trends and business insights.
• Develop and maintain Power BI dashboards, reports and visualisations.
• Work extensively with Microsoft Fabric, including Data Lake, Data Warehouse and data‑engineering capabilities.
• Build and optimise data models, datasets and ETL/ELT pipelines.
• Apply machine‑learning techniques for forecasting, prediction and optimisation.
• Collaborate with data scientists and data engineers to develop and deploy ML models.
• Use Python and related libraries for data analysis, statistical modelling and machine learning.
• Gather requirements from global business and IT teams and deliver data‑driven solutions.
• Ensure data quality, accuracy and consistency across analytics platforms.

Required profile

• 3+ years of experience in data analytics or business intelligence.
• Strong hands‑on experience with Power BI (DAX, Power Query, data modelling).
• Proficiency with Microsoft Fabric and modern Microsoft data platforms.
• Solid SQL skills and understanding of data‑warehouse concepts.
• Experience with machine learning / predictive analytics is highly preferred.
• Background in logistics, supply chain or transportation is a strong advantage.
• Excellent communication and stakeholder‑management abilities.

Required skills

• Microsoft Fabric
• Power BI
• DAX
• Power Query
• SQL
• Data Warehouse concepts
• Python
• Pandas
• Scikit‑learn
• Machine Learning
• ETL / ELT pipelines
• Data modelling
• Data visualisation

What we offer

• Permanent position with a reputable company.
• Opportunity to work on a large‑scale, global logistics project.
• Career growth in the IT and analytics field.