dbt Skill for Claude

Comprehensive dbt guidance: project structure, modeling, testing, CI/CD, production patterns. Targets Snowflake and BigQuery. Beginner-friendly with progressive scaling.

When to Use

Activate when: creating/modifying dbt models, choosing materializations, structuring layers, setting up tests, implementing CI/CD, configuring sources/freshness, writing Jinja macros, reviewing dbt projects, making analytics engineering decisions.

Skip when: basic SQL syntax, warehouse admin, raw pipeline config (Fivetran/Airbyte), BI tool config.

Core Principles

DRY via ref()/source() -- never hardcode table names
Single Source of Truth -- each concept defined once; staging = entry point, marts = consumer interface
Idempotent Transformations -- dbt run twice produces identical results
Test Everything -- every model has at minimum PK uniqueness and not-null tests
Progressive Complexity -- start with views/tables, add complexity when volume demands it

Project Structure

dbt_project/
├── dbt_project.yml
├── packages.yml
├── profiles.yml                 # local only, not committed
├── models/
│   ├── staging/                 # 1:1 with source tables
│   │   └── <source>/
│   │       ├── _<source>__models.yml
│   │       ├── _<source>__sources.yml
│   │       └── stg_<source>__<entity>.sql
│   ├── intermediate/            # business logic, joins, pivots
│   │   └── <domain>/
│   └── marts/                   # business-facing tables
│       └── <domain>/
│           ├── _<domain>__models.yml
│           ├── fct_<entity>.sql
│           └── dim_<entity>.sql
├── macros/
├── tests/
│   └── generic/
├── seeds/
├── snapshots/
└── analyses/

Layer Decision Matrix

| Layer | Materialization | Purpose | Naming | Tests | |-------|----------------|---------|--------|-------| | Staging | view | Clean/rename raw data, 1:1 with source | stg_<source>__<entity> | not_null, unique on PK | | Intermediate | ephemeral | Business logic, joins, pivots | int_<entity>_<verb>ed | Tested via downstream | | Marts | table/incremental | Business-facing facts and dimensions | fct_<entity>, dim_<entity> | Full coverage |

Materialization Decision Matrix

| Situation | Materialization | Why | |-----------|----------------|-----| | Staging models | view | Always fresh, minimal storage | | Intermediate logic | ephemeral | Zero cost, inlined as CTE | | Marts < 100M rows | table | Simple, fast reads | | Marts > 100M rows | incremental | Process only new/changed data | | SCD Type 2 | snapshot | Track historical changes |

ref() and source() Rules

source() only in staging -- staging is the sole gateway to raw data
ref() everywhere else
Never skip layers -- marts must not ref() staging directly
Never hardcode schema names

SQL Style

Leading commas, lowercase keywords, CTEs over subqueries
Explicit columns in marts (no select *), final CTE named final
4-space indentation, one column per line

Source Configuration

Define sources in _<source>__sources.yml with loaded_at_field and freshness thresholds. Configure warn_after and error_after per table.

| Concept | Snowflake | BigQuery | |---------|-----------|----------| | Top-level container | Database | Project | | Schema grouping | Schema | Dataset |

Warehouse Quick Reference

| Config | Snowflake | BigQuery | |--------|-----------|----------| | Profile type | snowflake | bigquery | | Auth | User/password or key-pair | OAuth or service account | | Schema gen | database.schema.model | project.dataset.model | | Incremental default | merge | merge | | Partitioning | Automatic micro-partitions | partition_by required for large tables | | Clustering | cluster_by (automatic) | cluster_by (manual) | | Cost model | Credits (compute time) | Bytes scanned / Slots |

Common Commands

| Command | Purpose | |---------|---------| | dbt build | Run + test in DAG order (recommended) | | dbt build --select +model | Build model and all ancestors | | dbt build --select model+ | Build model and all descendants | | dbt build --select tag:finance | All models tagged finance | | dbt build --select state:modified+ | Modified + descendants (Slim CI) | | dbt source freshness | Check source freshness | | dbt deps | Install packages | | dbt docs generate && dbt docs serve | Documentation site |

Gotchas

ref() only in staging-and-above, source() only in staging — using source() in marts bypasses the staging contract and breaks lineage
Incremental models without unique_key silently duplicate rows on re-runs — always set unique_key for merge strategy
ephemeral models can't be tested directly or selected with dbt test --select — test via downstream consumers
dbt run doesn't run tests — always use dbt build to get run + test in DAG order
--full-refresh on a large incremental model can blow warehouse credits — scope with --select first
Jinja whitespace control: {%- -%} vs {% %} — trailing whitespace breaks compile output silently
packages.yml version ranges (>=1.0,<2.0) can pull breaking changes — pin exact versions in production

-- WRONG: source() in marts (skips staging layer)
SELECT * FROM {{ source('stripe', 'payments') }}
-- RIGHT: ref staging model
SELECT * FROM {{ ref('stg_stripe__payments') }}

-- WRONG: incremental without unique_key (duplicates on re-run)
{{ config(materialized='incremental') }}
-- RIGHT: always specify unique_key
{{ config(materialized='incremental', unique_key='payment_id') }}

Scope Constraints

Advisory guidance for dbt project design; runs dbt commands only when the user asks
Warehouse specifics assume Snowflake or BigQuery — adapt for other adapters
Does not cover dbt Cloud account setup or warehouse-side schema/grant administration
Assumes source tables exist; raw ingestion (Fivetran, Airbyte, etc.) is out of scope

Reference Files

Load on demand when detailed guidance is needed:

| Reference | Topics | |-----------|--------| | Testing & Quality | Schema/generic/singular/unit tests, dbt-expectations, layer strategy | | CI/CD & Deployment | Slim CI, GitHub Actions, dbt Cloud, environments, blue/green, SQLFluff | | Jinja, Macros & Packages | Jinja fundamentals, custom macros, packages, debugging | | Incremental & Performance | Microbatch, merge, delete+insert, insert_overwrite, warehouse tuning | | Data Quality & Observability | Source freshness, Elementary, anomaly detection, alerting, incidents | | Semantic Layer & Governance | MetricFlow, contracts, versions, access controls, dbt Mesh |

License

Apache License 2.0. See LICENSE file for full terms.