Netflix’s Data Bridge simplifies the complex process of moving data across its various storage systems. Historically, the Netflix data ecosystem involved multiple datastores, like Cassandra and Google Sheets, requiring engineers to navigate a fragmented landscape of tools. This fragmentation led to cognitive overload for users, operational inefficiencies, unreliable data governance, and poor discoverability of the right tools for data movement tasks. Users often found themselves tangled in intricate commands rather than focusing on the intent of their data movements. Data Bridge was developed to create a unified control plane that standardizes data movement within Netflix. It acts as an abstraction layer, orchestrating existing systems rather than replacing them. The platform allows users to move data without needing to understand the underlying technical details, thereby decoupling user intent from implementation. It supports both batch and streaming technologies and provides interfaces tailored to different user needs—ranging from a web UI for non-technical users to a GraphQL API for developers. The design of Data Bridge emphasizes clarity and simplicity. It includes a registry that maps user intents to the appropriate data movement systems. Users can create and manage data movements with minimal coding effort, thanks to a no-code and low-code approach. The system is built to enforce security and governance policies consistently, allowing Netflix to maintain control over its data while streamlining operations. The article details how the platform's architecture enables developers to add new connectors easily, enhancing its adaptability to evolving data needs.