ETL Design

Purpose

Design robust ETL (Extract-Transform-Load) pipelines that move data from source systems to target systems with appropriate transformations, error handling, and performance optimization.

When to Use

• Building data warehouses or data lakes
• Migrating data between systems
• Integrating multiple data sources
• Creating analytics pipelines
• Implementing data synchronization
• Building real-time or batch data flows

Key Capabilities

1. Pipeline Architecture - Design scalable, maintainable ETL workflows
2. Incremental Loading - Implement efficient delta/change detection strategies
3. Data Transformation - Clean, enrich, and transform data between systems