Concurrent Data Processing Pipeline with Fault Tolerance

Create a robust data processing pipeline using Python's concurrent.futures and asyncio that can handle large-scale data transformations with built-in fault tolerance. Implement a dynamic worker pool with adaptive scaling, circuit breaker patterns for external service calls, and comprehensive error recovery mechanisms. Design the system to support both streaming and batch processing with configurable retry strategies and detailed execution tracking.