Urban energy systems play a pivotal role in addressing global sustainability challenges, significantly impacting energy consumption and greenhouse gas emissions. This thesis introduces the development of a modular backend system, utilizing a microservice architecture, to automate the creation of urban energy scenarios. The research focuses on resolving critical issues of data accessibility, heterogeneity, and scalability in urban energy system modelling. The methodology is structured into distinct phases. A scalable microservice-based architecture was designed to manage and streamline geospatial data processing and enrichment. Advanced data validation techniques and spatial interpolation methods were employed to address gaps in building attributes. The system generates standardized GeoJSON outputs, which are stored in a database and serve as inputs for the co-simulation of multi-energy systems, ensuring seamless integration and practical application.