Designing technology for sociotechnical problems is challenging due to the heterogeneity of stakeholders' needs, the diversity among their values and perspectives, and the disparity in their technical skills. Careful considerations are needed to ensure that data collection is inclusive and representative of the target populations. It is also important to employ data analysis methods that are compatible with users' technical skills and are capable of drawing a representative picture of people's values, priorities, and needs. However, current technical solutions often fail to meet these critical requirements. In this article, we present a set of empirically-driven design considerations for building technological interventions to address sociotechnical issues. We then discuss open challenges and tradeoffs around privacy, ethics, bias, uncertainty, and trust. We conclude with a call to action for researchers to advance the domain knowledge and improve our technological arsenal for addressing sociotechnical problems.