Pattern detection over streams of events is gaining more and more attention, especially in the field of eCommerce. Our industrial partner Cdiscount, which is one of the largest eCommerce companies in France, wants to use pattern detection for real-time customer behavior analysis. The main challenges to consider are efficiency and scalability, as the detection of customer behavior must be achieved within a few seconds, while millions of unique customers visit the website every day, each performing hundreds of actions. In this paper, we present our approach to large-scale and efficient pattern detection for eCommerce. It relies on a domain-specific language to define behavior patterns. Patterns are then compiled into deterministic finite automata, which are run on a Big Data streaming platform to carry out the detection work. Our evaluation shows that our approach is efficient and scalable, and fits the requirements of Cdiscount.