dbt Consulting
Build data models your team can test, explain and change with confidence
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Analytics Engineering with dbt
We help teams build and improve dbt projects with maintainable models, tests, documentation and controlled deployment workflows.
Starting fresh or working through an existing project, we connect business definitions to SQL models and put tests and review steps around changes.
Our dbt Services
dbt Project Setup
Set up folders, naming conventions, tests and CI/CD so the team has a consistent way to develop and release models.
Model Development
Build staging, intermediate and mart models around agreed business definitions, with reusable macros and documented dependencies.
Testing & Data Quality
Add key, relationship and business-rule tests, with freshness checks and a process for investigating failures.
Migration & Optimization
Move existing SQL into dbt, reconcile the results and tune expensive models. Choose incremental processing where it fits the data and refresh requirements.
Why Choose dbt?
Version-Controlled Transformations
Keep transformation logic in Git so the team can review changes, trace decisions and restore an earlier version.
Built-in Testing
Use dbt tests to check defined expectations before changes reach reporting. Business experts still validate that the measures represent the intended concepts.
Auto-Generated Documentation
Publish model and column descriptions alongside dependency diagrams so developers and report builders can understand the project.
Workload-aware model design
Choose views, tables and incremental models to balance refresh needs, query performance and Snowflake compute cost.
Accelerate with Our dbt Jumpstart
Get started faster with our pre-built dbt project template. Includes coding standards, testing patterns, and CI/CD configuration built from real-world Snowflake project experience.
Learn About dbt JumpstartFrequently Asked Questions
What is dbt and how does it fit in the modern data stack?
dbt organizes warehouse transformations into models that can be tested, documented and reviewed in Git. It sits after ingestion and before reporting: tools such as Fivetran load the source data, and dbt turns it into models that BI tools can use.
Should I use dbt Core or dbt Cloud?
With dbt Core, your team manages execution, scheduling and CI. The managed dbt platform, often called dbt Cloud, brings development and deployment workflows together with a browser-based IDE. We help choose the fit for your team, operating model and budget.
How long does it take to implement dbt?
Timing depends on source readiness, transformation complexity, testing and deployment requirements. We define the first phase after reviewing your project; the Jumpstart can reduce repeated setup work.
Can dbt work with Snowflake?
Yes. dbt runs SQL transformations using Snowflake compute. We configure development and deployment access, choose how models are built and test their results and performance against your reporting needs.
What's the difference between dbt and Coalesce?
For a Snowflake project, both can manage data transformations. dbt centers development on code and Git review; Coalesce provides a visual, column-aware development interface. We work with both and help choose around your team's skills, review process and existing investment.
Related Insights
Make your dbt project easier to maintain
Discuss your models, testing gaps and deployment workflow with our team.
Schedule a discovery call