Data Engineering ETL API Specification

Interactive documentation for the Data Engineering ETL API, based on OpenAPI 3.0.3 specification.

This API specification serves as a universal guide for data engineers implementing ETL (Extract, Transform, Load) processes. It is based on best practices abstracted from real-world implementations and provides a standardized approach to building robust, maintainable, and scalable data pipelines.

Key Features

  • Comprehensive Logging: Detailed logging of all ETL operations
  • Error Handling: Robust error handling with detailed error reporting
  • Delta Updates: Support for incremental data processing
  • Timestamp Handling: Proper management of timestamps for data lineage and auditing
  • Partitioning: Advanced partitioning capabilities for optimized data storage and retrieval
  • Metadata Management: Tracking of ETL events, checkpoints, and metrics

API Documentation

The interactive API documentation below provides detailed information about all available endpoints, request parameters, and response schemas.

Note: This Swagger UI interface allows you to explore the API endpoints interactively. You can expand each endpoint to see detailed parameter descriptions, request/response schemas, and even test the endpoints directly from the browser.

API Overview

ETL Events

Track all significant events in your ETL pipeline with detailed timestamps, status information, and contextual metadata.

Checkpointing

Implement robust checkpointing mechanisms to track individual entity processing and enable efficient recovery from failures.

Metrics Collection

Collect and analyze performance metrics to optimize your ETL processes and identify bottlenecks.

Pagination Support

Handle large datasets efficiently with built-in pagination support for all data extraction operations.

Implementation Guidelines

Best Practices
  1. Idempotency: Design all operations to be safely repeatable
  2. Error Handling: Implement comprehensive error catching and logging
  3. Monitoring: Set up alerts and dashboards for key metrics
  4. Documentation: Keep API documentation in sync with implementation
  5. Testing: Write unit and integration tests for all endpoints
Important: This API specification is designed to be cloud-agnostic and can be implemented on any platform (GCP, AWS, Azure, on-premises). Adapt the examples to your specific infrastructure requirements.