BigQuery ETL Core

About

BigQuery ETL Core serves as the essential framework for navigating and contributing to Mozilla's data transformation pipelines. It provides comprehensive guidance on project organization, ensuring that table definitions, SQL queries, and metadata follow strict versioning and naming standards. By centralizing resources for schema discovery, data privacy protocols, and BigQuery optimization techniques like partitioning and clustering, this skill enables developers to build maintainable and performant data models. It functions as a base layer that informs query writing, testing, and metadata management, making it indispensable for anyone working within complex data repository structures.

Key Features

• Strict privacy guidelines and PII handling protocols
• Standardized directory and table naming conventions
• Library of common Mozilla-specific UDFs (mozfun)
• Multi-source schema discovery and documentation prioritization
• 0 GitHub stars
• Optimized partitioning and clustering implementation patterns

Use Cases

• Finding and validating schema descriptions for complex data models
• Navigating and understanding the structure of a large-scale SQL repository
• Ensuring data privacy compliance during table construction