Transformation

dbt

The standard for analytics engineering — SQL transformations done right

https://www.getdbt.com

What It Is

dbt (data build tool) is the industry standard for transforming data inside warehouses using SQL. It brings software engineering best practices — version control, testing, documentation, and CI/CD — to the analytics workflow. dbt allows analysts and engineers to collaboratively build reliable, modular data transformations that serve as the foundation for all downstream analytics and reporting.

How We Use It

dbt is at the center of every analytics engineering project we deliver. We use it for building transformation layers in Snowflake, BigQuery, ClickHouse, PostgreSQL, and Redshift. Our work covers initial project setup, model architecture (staging/intermediate/marts), testing strategies, documentation, CI/CD pipeline configuration, and performance optimization. We work with both dbt Core and dbt Cloud.

Our Expertise

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Project Architecture

We design dbt projects with clean staging/intermediate/marts layer separation, consistent naming conventions, and proper ref() and source() usage.
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Testing & Quality

We implement schema tests, data tests, custom generic tests, and dbt expectations. Every model is tested before it reaches production.
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CI/CD Pipelines

We set up dbt CI/CD with GitHub Actions, GitLab CI, or dbt Cloud: slim builds, deferred state comparisons, and automated documentation deployment.
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Performance Optimization

We optimize dbt models for warehouse-specific performance: incremental strategies, materialization selection, and query profiling.
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Documentation & Lineage

We build comprehensive dbt documentation with model descriptions, column descriptions, and exposure definitions for full data lineage.