dbt specialists for your dedicated team.

Where dbt fits in a long-term product team.

What dbt really introduces is software practice to analytics. Transformations become reviewable code with tests and a dependency graph, which means a change to a definition of revenue can be traced to everything it affects instead of discovered by a finance team in a meeting.

Its tests are the underused part. Checking that a key is unique, that a join kept every row and that a value falls in an expected range catches the silent failures that make a dashboard confidently wrong, the kind that costs most and is noticed last.

What your dedicated team does with dbt.

A dbt project is a codebase and decays like one. Models pile up, tests stop being added, and people look at the lineage graph without trusting it. Review discipline is what prevents that, and review discipline requires reviewers who will still be here.

The transformation layer is only as good as what feeds it, so ingestion and modelling usually belong to one team, often a dedicated software development team when the scope spans both.

Common dbt use cases.

• One definition of a metric Revenue or active user defined once in a model, so two reports stop disagreeing.
• Catching silent data failures Tests on uniqueness, nulls and row counts that fail the build before they reach the dashboard.
• Lineage people can read A documented graph from source to report, so the effect of a change can be assessed before it ships.

Adding dbt skills to your team.

Analytics engineering is assigned in a dedicated data engineering team, working in your warehouse and your repository.

dbt specialists join your team remotely as dedicated, full-time team members, selected, employed and managed by us in Chiang Mai and Bangkok. Companies that hire offshore developers through Azendo add the skill at the next monthly cycle.