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Sharing real-time data originating from connected devices is crucial to real-world Internet of Things (IoT) applications, especially using artificial intelligence/machine learning (AI/ML). Such IoT data are typically shared with multiple parties for different purposes based on data contracts. However, supporting these contracts under the dynamic change of IoT data variety and velocity faces many challenges when such parties (aka tenants) want to obtain data based on the data value to their specific contextual purposes. This work proposes a novel dynamic context-based policy enforcement framework to support IoT data sharing based on dynamic contracts. Our enforcement framework allows IoT Data Hub owners to define extensible rules and metrics to govern the tenants in accessing the shared data on the Edge based on policies defined in static and dynamic contexts. For example, given the change of situations, we can define and enforce a policy that allows pushing data to some tenants via a third-party means, while typically, these tenants must obtain and process the data based on a pre-defined means. We have developed a proof-of-concept prototype for sharing sensitive data such as surveillance camera videos to illustrate our proposed framework. Our experimental results demonstrated that our framework could soundly and timely enforce context-based policies at runtime with moderate overhead. Moreover, the context and policy changes are correctly reflected in the system in nearly real-time.