Many of today''s embedded systems are data-intensive. They are moreover more and more often operating in an open, dynamic environment with varying processing workloads and changing resource availability. Dataflow models of computation are well-suited for the model-driven design of data-intensive embedded systems. Traditional dataflow models like synchronous dataflow cannot efficiently cope with the dynamics of modern systems. Novel computational models such as scenario-aware dataflow have been developed to address this challenge. In this presentation, I will present an overview of model-driven embedded-system design using dataflow models, surveying the state of the art in system synthesis and highlighting some remaining challenges.