Quantitative Data Intelligence (QDI) - Data Analyst

Inetum is a European leader in digital services , supporting organizations as they navigate continuous technological change. The company helps clients accelerate their digital transformation through a broad portfolio that includes consulting, application services, digital engineering, cloud, cybersecurity, platforms, and infrastructure services The Quantitative Data Intelligence (QDI) team is responsible for delivering data, insights, and analytical solutions to support the Global Markets Front Office. Our mission is to build and maintain robust data platforms by integrating information from multiple sources and transforming it into meaningful insights through analytics, reporting, and data visualization. We work in close partnership with business stakeholders, sales teams, and traders, ensuring agile and impactful delivery of information to support decision-making. Key responsibilities include: Design, develop, and maintain data solutions that support Front Office activities. Build and optimize data pipelines, ETL processes, and data warehousing environments. Develop dashboards, reports, and analytical tools to generate actionable business insights. Collaborate directly with business sponsors, sales teams, and traders to understand requirements and deliver value-driven solutions. Contribute to the evolution of data and analytics technologies, leveraging tools such as Python , SQL , Tableau , Power BI , APIs, and AI-powered chatbot solutions. Ensure data quality, consistency, and accessibility across different platforms and data sources. Bachelor's degree in Engineering, Economics, Computer Science, Mathematics, Statistics , or a related field. Minimum of 2 years of professional experience with Tableau , including dashboard development and data visualization best practices. Professional experience in data analysis and programming , preferably using Python . Strong analytical and problem-solving skills, with the ability to synthesize complex information into clear and actionable insights. Knowledge of SQL and data modeling concepts. Understanding of descriptive statistics and hypothesis testing is considered a plus. Experience with Big Data technologies , such as PySpark, Presto, and Airflow , is a plus. Experience with Power BI , APIs, or cloud-based data platforms is an advantage. Language Skills English: Advanced / Fluent (mandatory) Important: Hybrid Work (50% of homeworking per month); First 4 to 8 weeks, 100% in the office (depending on progression).