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dbt-migration

Automate dbt project migration across platforms and versions with validation.

8|Updated Feb 23, 2026
Search Tags:#migration#cross-platform#dbt#project upgrade#sql translation#legacy SQL
One-click install
npx skills add https://github.com/rittmananalytics/wire-plugin --skill dbt-migration-rittmananalytics
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dbt-migration
Source: https://github.com/rittmananalytics/wire-plugin/tree/main/skills/dbt-migration
Command: npx skills add https://github.com/rittmananalytics/wire-plugin --skill dbt-migration-rittmananalytics

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill addresses the complexities of migrating dbt projects between data warehouses and upgrading dbt versions, ensuring a systematic workflow with validation at each step.

Core Features & Use Cases

  • Cross-Platform Migration: Facilitate moving dbt projects between BigQuery, Snowflake, and Databricks with dialect translation and macro adaptation.
  • Version Upgrades: Manage upgrades between dbt versions, handling schema changes, macro API updates, and package compatibility.
  • Legacy SQL Migration: Convert stored procedures, views, and raw SQL scripts into modular dbt models with procedural logic translation.
  • Use Case: Transition a monolithic stored procedure to a series of dbt models compatible with Snowflake, verifying outputs at each phase.

Quick Start

Use the dbt-migration skill to assess your current project, then configure your target platform, recompile, fix errors iteratively, and validate results against pre-migration tests.

Frequently Asked Questions about dbt-migration

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I migrate dbt projects between BigQuery, Snowflake, and Databricks?▼

Migrate dbt projects between data warehouses by configuring your target platform, translating SQL dialects, adapting macros, and iteratively recompiling to ensure platform compatibility.

What is the best way to upgrade dbt versions without breaking existing models?▼

Upgrade dbt versions systematically by handling schema changes, updating macro APIs, verifying package compatibility, and validating results against pre-migration tests to prevent broken models.

Can I convert legacy SQL stored procedures into modular dbt models?▼

Convert legacy SQL stored procedures, views, and raw scripts into modular dbt models by translating procedural logic into dbt-compatible workflows and verifying outputs at each phase.

Does the dbt migration process validate outputs against pre-migration tests?▼

The dbt migration process validates correctness by running recompiled models and comparing validation results against pre-migration tests at each step to reduce migration risks.

How do I fix errors when translating SQL dialects during a cross-platform dbt migration?▼

Fix SQL dialect translation errors during cross-platform dbt migration through an iterative process of recompiling code, classifying errors, and applying platform-specific macro adaptations.

What steps are required to transition a monolithic stored procedure to dbt on Snowflake?▼

Transitioning a monolithic stored procedure to Snowflake-compatible dbt models requires assessing the current project, translating procedural logic into modular models, and verifying outputs iteratively.

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