Cloud object stores are versatile storage services that support a wide range of use cases. They simplify the management of large blocks of data at scale and are becoming the de facto storage choice for Big Data analytics platforms. To build these services cost-effectively, cloud vendors use hard disk drives (HDDs) in their object store deployments. However, the lower performance of HDDs affect tenants who have strict performance requirements for their Big Data applications. The use of faster storage devices such as solid state drives (SSDs) is thus desirable by the tenants, but incurs significant maintenance costs to the provider. The tiered object store detailed here is designed for the cloud, taking into account both fast and slow storage devices. The resulting hybrid store exposes the tiering to tenants with a dynamic pricing model based on the tenants' usage and the provider's desire to maximize profits. The tenants leverage knowledge of their workloads and current pricing information to select a data placement strategy that would meet the application requirements at the lowest cost. This approach allows both a service provider and its tenants to engage in a pricing game, which yields a win-win situation.