Data Engineering Data Pipeline

Comprehensive data pipeline guidance with actionable patterns, clear examples, and strong observability focus

• +Provides detailed architecture patterns (ETL, ELT, Lambda, Kappa, Lakehouse) with selection criteria
• +Includes concrete code examples with error handling and data quality validation
• +Covers end-to-end concerns: ingestion, transformation, monitoring, and cost optimization
• -Declares shell execution permission without clear justification in instructions
• -Example code references non-existent modules without setup context