Dynamic Multi-Source Data Pipeline with Error Handling

Design a robust Python data pipeline that can simultaneously ingest data from multiple sources (REST APIs, CSV files, and SQL databases) with comprehensive error handling and logging. Implement automatic retry mechanisms, data validation, and transformational logic that can handle different data schemas. The solution should include rate limiting, connection pool management, and the ability to resume interrupted transfers. Create a modular architecture that allows easy addition of new data sources and supports parallel processing.