What problem does it solve? Building correct Dataform pipelines for BigQuery requires deep knowledge of SQLX syntax, incremental table semantics, source declarations, and GCS ingestion patterns. This Skill guides an AI agent through the full lifecycle of creating, modifying, and validating Dataform projects so pipelines compile cleanly and follow BigQuery best practices. ## Core Features & Use Cases - Pipeline Generation: Creates SQLX actions, source declarations, and workflow_settings.yaml configurations for new or existing Dataform repositories. - Incremental & GCS Ingestion: Enforces correct use of incremental types for append operations and external table definitions for loading CSV data from GCS into BigQuery. - Validation Workflow: Compiles pipelines with dataform compile, validates with dry runs and bq query, and applies automatic data cleaning and SQL optimization rules. - Use Case: Ask the agent to build a Dataform pipeline that ingests CSV files from a GCS bucket into a partitioned BigQuery table, and it will initialize the project, declare sources, write the SQLX files, and validate everything with dry runs. ## Quick Start Create a Dataform pipeline that loads my GCS CSV files into a new BigQuery table and validate it with a dry run.
