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Function-as-a-Service or FaaS is a popular delivery model of serverless computing where developers upload code to be executed in the cloud as short running stateless functions. Using smaller functions to decompose processing of larger tasks or workflows introduces the question of how to instrument application control flow to orchestrate an overall task or workflow. In this paper, we examine implications of using different methods to orchestrate the control flow of a serverless data processing pipeline composed as a set of independent FaaS functions. We performed experiments on the AWS Lambda FaaS platform and compared how four different patterns of control flow impact the cost and performance of the pipeline. We investigate control flow using client orchestration, microservice controllers, event-based triggers, and state-machines. Overall, we found that asynchronous methods led to lower orchestration costs, and that event-based orchestration incurred a performance penalty.