dbt

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dbt Expert Engineer Skill - Comprehensive guide for dbt development best practices, command execution, and environment configuration Use when: - Running dbt commands (debug, compile, run, test, show) - Setting up Issue-specific targets in profiles.yml - Working with Databricks SQL dialect in dbt

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Added on2026-02-21

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SKILL.md Content

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dbt Expert Engineer Skill

This skill provides a comprehensive guide for dbt development.

1. dbt Command Basics

1.1. Required Options

Always specify these options with dbt commands:

sh

--profiles-dir ~/.dbt --no-use-colors

1.2. Connection Verification

Always verify connection at work start:

sh

dbt debug --profiles-dir ~/.dbt --no-use-colors

1.3. Ad-hoc Query Execution

Use

dbt show

command for ad-hoc queries in dbt:

sh

# Basic query execution
dbt show --inline "select 1 as test, current_timestamp() as now" --profiles-dir ~/.dbt --no-use-colors

# Specify row limit (default is 5)
dbt show --inline "select * from table_name" --limit 10 --profiles-dir ~/.dbt --no-use-colors

# Reference dbt models
dbt show --inline "select * from {{ ref('model_name') }}" --profiles-dir ~/.dbt --no-use-colors

# Direct reference using catalog.schema.table format
dbt show --inline "select * from catalog_name.schema_name.table_name" --limit 3 --profiles-dir ~/.dbt --no-use-colors

Notes:

Explicit LIMIT in query conflicts with
```
--limit
```
option and causes error
DDL commands (SHOW statements, etc.) cause syntax error due to auto-LIMIT

2. Verification Procedures

2.1. Verification When dbt run is Prohibited

Verification steps when

dbt run

cannot be executed to avoid production impact:

Edit model

Generate SQL with

dbt compile --profiles-dir ~/.dbt --no-use-colors

Get generated SQL from
```
target/compiled/
```
Verify with
```
bq query
```
or
```
databricks
```
command (recommend using LIMIT)

2.2. Verification When dbt run is Allowed

Verification steps when

dbt run

is allowed in development/sandbox environments:

Edit model

Execute

dbt run --select +model_name --profiles-dir ~/.dbt --no-use-colors

Execute

dbt test --select +model_name --profiles-dir ~/.dbt --no-use-colors

Query generated table directly if needed

Notes:

Use
```
--select
```
option to limit scope
For model AND tag conditions, use
```
--select "staging.target,tag:tag_name"
```

3. Issue Work Target Setup

Always set up Issue-specific target before

dbt run

during Issue work.

3.1. Setup Procedure

Read
```
~/.dbt/profiles.yml
```
and check existing settings
Add Issue-specific target if not exists, based on existing
```
dev
```
target

yaml

my_databricks_dbt:
  outputs:
    dev:
      # Existing settings...
    issue_123: # Name based on issue number
      catalog: dbt_dev_{username} # Same as dev
      host: dbc-xxxxx.cloud.databricks.com # Same as dev
      http_path: /sql/1.0/warehouses/xxxxx # Same as dev
      schema: dwh_issue_123 # Include issue number in schema name
      threads: 1
      token: dapixxxxx # Same as dev
      type: databricks
  target: dev

Then switch with

--target

option when executing dbt commands

sh

# Execute with issue_123 target
dbt run --select +model_name --target issue_123 --profiles-dir ~/.dbt --no-use-colors

# Verify connection
dbt debug --target issue_123 --profiles-dir ~/.dbt --no-use-colors

3.2. Notes

Keep target name and schema name consistent with issue number
Manually delete unused schemas after work completion
Intermediate layer auto-generates as
```
{schema}_dbt_intermediates
```

4. Databricks SQL Dialect

Full-width column names require backticks
Column names and catalog names with hyphens require backticks

sql

-- Reference catalog name with hyphen
select * from `catalog-name`.schema_name.table_name;

-- Reference full-width column name
select `full-width column` from table_name;

5. Response Format

text

[Documentation-based response]

Source: [source_url]
Fetched: [fetched_at]

dbt