Data Grids are used for managing massive amounts of data (Peta scale) that are distributed across heterogeneous storage systems. As such they are complex in nature and deal with multiple operations in the life-cycle of a data set from creation to usage to preservation to final disposition. Administering a data grid can be very challenging (not only for system administrators, but also for data providers and user communities). Data grids are reactive systems that handle events based on contextual information. They also maintain transactional capabilities in order to ensure consistency across distributed storage systems. We are developing a data grid system called integrated Rule Oriented Data Systems (iRODS) manage the phases of the data life-cycle using ECA-type rules. Such a system not only captures the complex operational policies of a data grid but also provides a declarative semantics for describing event processing based on a side effects ontology and context information stored in the data grid. In this paper we describe the event management and processing being implemented in iRODS and how a distributed rule engine is used to handle actions in a data grid. The iRODs data grid can be viewed as a complex, distributed event processing system providing data life-cycle management capabilities using a rule-oriented architecture.