From snowflake-skills
Converts legacy SQL from stored procedures, views, or raw files to modular dbt models, building sources, staging, intermediate, and mart layers incrementally with validation.
npx claudepluginhub altimateai/data-engineering-skills --plugin dbt-skillsThis skill uses the workspace's default tool permissions.
**Don't convert everything at once. Build and validate layer by layer.**
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Don't convert everything at once. Build and validate layer by layer.
cat <legacy_sql_file>
Identify all tables referenced in the query.
# Search for existing models/sources that reference the table
grep -r "<table_name>" models/ --include="*.sql" --include="*.yml"
find models/ -name "*.sql" | xargs grep -l "<table_name>"
For each table referenced in the legacy SQL:
Only proceed to intermediate/mart layers after all dependencies exist.
# models/staging/sources.yml
version: 2
sources:
- name: raw_database
schema: raw_schema
tables:
- name: orders
description: Raw orders from source system
- name: customers
description: Raw customer records
One staging model per source table. Follow existing project naming conventions.
Build before proceeding:
dbt build --select <staging_model>
Extract complex joins/logic into intermediate models.
Build incrementally:
dbt build --select <intermediate_model>
Final business-facing model with aggregations.
# Build entire lineage
dbt build --select +<final_model>
dbt show --select <final_model>
{{ config(materialized='ephemeral') }}{{ var("name") }}