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Reusable API Ingestion Framework

Built enterprise-grade API ingestion frameworks handling token refresh, pagination, schema evolution, and fault tolerance.

PythonREST APIsAzureData Integration
GitHub
Reusable API Ingestion Framework

Overview

Developed reusable API ingestion frameworks for enterprise clients, enabling efficient and reliable data extraction from third-party and internal REST APIs.

Technical Challenges Solved

  • Token Management: Automated OAuth token refresh and management for secure API access
  • Pagination Handling: Generic pagination logic supporting cursor-based, offset, and page-number pagination styles
  • Dynamic Schema Handling: Schema evolution detection and handling for APIs with changing response structures
  • Fault Tolerance: Retry logic, circuit breakers, and graceful degradation for unreliable API endpoints

Architecture

The framework was designed with modularity in mind:

  • Configurable connector classes for different API authentication methods
  • Pluggable transformation layers for data normalisation
  • Integration with Azure Data Factory and Databricks for orchestration
  • Comprehensive logging and monitoring

Technologies

  • Python
  • Azure Data Factory
  • Databricks
  • REST API integration patterns

Results

  • Reduced development time for new API integrations by 60%
  • Improved reliability of data ingestion processes
  • Enabled consistent data quality across multiple source systems