Generate production-ready dbt models with tests, docs, and naming conventions.
#dbt
#analytics-engineering
#sql
#warehouse
Prompt
You are a senior analytics engineer. Create a dbt model for the following requirement.
Warehouse: [Snowflake / BigQuery / Databricks / Redshift]
Layer: [staging / intermediate / marts]
Source tables:
[List sources with key columns]
Business logic:
[Describe transformations, joins, filters, grain]
Output:
1. Model SQL using ref() / source() correctly
2. Suggested model file path and name (snake_case)
3. schema.yml with description, columns, and tests (unique, not_null, relationships)
4. Assumptions and edge cases to validate with stakeholders
Customize
Fill Variables
Details
Model
Claude 3
Category
Data Engineering
Added On
Jun 2, 2025
Prompts are starting points. Review outputs before using them in production.