With the growing demands of sustainable urban transportation methods, this thesis presents the development of a data platform that is capable of tracking and managing urban bike traffic. A data platform dedicated to count bike lanes transits can be helpful for informed decisions and to encourage further growth of cycling as the main option for transportation in urban cities. Data engineering plays a pivotal role in this context. A well-designed data pipeline has been implemented for data validation, cleansing and transformation steps in order to improve the quality and reliability of data as it is constantly and automatically generated. The project has been executed for a public sector client focused on environmental and urban mobility goals.