Brussels Metropolitan Area
I thrive at the intersection of data, technology, and creative problem-solving. As a data engineer, I build solutions that not only work but evolve: systems that adapt, reveal insights. I bring curiosity, strategy, and an intuitive sense for connections: between systems, between people, between ideas. Always learning, always questioning, always looking for the next challenge.
Developed end to end processes for data integration, transformation, and governance within a cloud-based environment. The primary focus was on contributing to the development of a comprehensive cloud data platform tailored to the needs of public administrations. This platform was designed to centralize and optimize data processing workflows, ensuring efficient data management and governance practices while leveraging the scalability and flexibility offered by cloud technologies. Responsibilities: ● Developed processes for collecting, cleaning, and transforming diverse data into a cohesive warehouse. ● Contributed to analyzing, structuring, and modeling information to meet the needs of public administrations. ● Managed data governance, security, and compliance to ensure adherence to defined standards. ● Monitored tools and infrastructure for optimal data processing, conducting evolutionary maintenance. ● Designed and configured Azure services, leveraging Terraform scripting for infrastructure as code, to establish a robust and scalable cloud data platform. ● Conducted workshops to instruct clients on the effective utilization of tools such as Snowflake, DBT, and the Azure Cloud Platform. Technological Environment: : Azure Cloud (Azure Data Factory, Azure DevOps, AD), Snowflake, DBT, Terraform, Airflow, Kubernetes, Python, SQL.
Infrabel Contributed to projects focused on process automation and data quality improvement within the railway infrastructure domain. One of the key goals of this role was to mentor newcomers trainees on their yearly traineeship program. This program aimed to accompany them through their first development role, share good practices, and collaborate on projects and peer reviews, ultimately fostering their growth and development within the team. Responsibilities: ● Designed and developed an automated quality review system in Python, streamlining peer review processes and ensuring data integrity within the railway infrastructure domain. ● Designed and developed ETL pipelines leveraging SAP HANA and SAP BODS to automate data extraction, transformation, and loading processes, enhancing efficiency and accuracy within the railway infrastructure domain. ● Mentored junior developers and trainees on the yearly traineeship program, providing guidance, sharing best practices, and collaborating on projects, peer reviews, and technical documentation. Digilab Developed an AI Fake News Detector. Collaborating closely with the Digilab team at Sopra Steria, our objective was to craft a REST API tool to facilitate predictive modeling of fake news, leveraging advanced machine learning techniques. Responsibilities: ● Crafted a REST API tool to facilitate predictive modeling of fake news, utilizing Python for data manipulation, SQL Alchemy for database interaction, and Flask and Django for web development. ● Leveraged Scikit-learn for machine learning tasks, implementing algorithms to analyze and classify news articles based on various features. Technological Environment: Python, SQL, Flask, Django, Scikit-learn
Joined the JobYourself cooperative as an entrepreneur. Jobyourself offers global support and a secure framework to develop innovative projects.
Contributed to projects aimed at supporting startups through data-driven insights and solutions. One of the primary objectives of these projects was to create a centralized database for reporting and analysis, facilitating investment decisions and fostering growth within the startup ecosystem. Responsibilities: ● Worked on projects involving the analysis of startup ecosystem data to identify trends, opportunities, and potential areas for improvement. ● Utilized web scraping techniques to gather data from various online sources for analysis and modeling purposes. ● Developed dashboards and visualization tools to communicate insights effectively to stakeholders using Power BI. ● Conducted data analysis and modeling tasks using Python and relevant libraries such as Pandas for data manipulation and Scikit-learn for machine learning tasks. Technological Environment: Python, Pandas, Scikit-learn, Web scraping, Power BI