Most applications manipulate structured data. Modern languages and platforms provide collection frameworks with basic data structures like lists, hashtables and trees. These data structures come with a range of predefined operations which include sorting, filtering or finding elements. Such bulk operations usually traverse the entire collection and process the elements sequentially. Their implementation often relies on iterators, which are not applicable to parallel operations due to their sequential nature. We present an approach to parallelizing collection operations in a generic way, which can be used to factor out common parallel operations in collection libraries. Our framework is easy to use and straightforward to extend to new collections. We show how to implement concrete parallel collections such as parallel arrays and parallel hash maps, proposing an efficient solution to parallel hash map construction. Finally, we give benchmarks showing the performance of parallel collection operations.