Data engineering plays a pivotal role in advancing sustainability efforts by providing the tools and frameworks necessary to collect, process, and analyze vast amounts of environmental data. This chapter explores the essential role of data engineering in building resilient, sustainable systems across various sectors, including energy, agriculture, water management, and waste reduction. By focusing on the core principles of data engineering, including data collection, storage, integration, and analysis, this chapter highlights how these practices are fundamental to driving informed decision-making for sustainable development. It also delves into the challenges faced in integrating disparate data sources, ensuring data quality, and implementing scalable solutions that can adapt to the evolving demands of sustainability. Through real-world case studies, the chapter illustrates how effective data engineering can optimize resource management, improve environmental monitoring, and support the transition to a low-carbon economy. Furthermore, the chapter emphasizes the importance of cross-disciplinary collaboration and innovation in leveraging data engineering to address the pressing environmental challenges of today and tomorrow. As the world moves towards a more sustainable future, data engineering will continue to be at the forefront of enabling systems that are not only efficient but also resilient to the complexities of a changing environment.