Given the incredible popularity of video games in contexts from entertainment to education, and the capacity of internet-connected games to record fine-grained telemetry data, there exists an unprecedented opportunity to investigate gameplay behaviors, outcomes, and their relationships to learning processes. However, with these opportunities come the need for technical infrastructures to manage the collection and analysis of massive amounts of game event data. In this work, we build upon existing literature to develop an architectural design for such infrastructure. We address issues of play data collection across many games; regular, repeatable extraction of gameplay features from raw data; and access to data for secondary analyses. In addition, we describe an implementation of this infrastructure and provide real-world examples of the implementation’s usage in prior large-scale analysis work.