dbt
transformation
dbt Consulting & Implementation
Most dbt projects rot into a tangle of untested models nobody trusts. We build the one your team actually does.
dbt is the industry standard for data transformation. It lets you define business logic in SQL, version control it like code, and test it automatically. We implement dbt the way it was meant to work — a tested, documented modelling layer your team trusts — not as a glorified SQL runner. Senior engineers, production-grade from the first commit.
dbt · live signal
What we've shipped with dbt
Point of view
Why most dbt projects rot
dbt is easy to start and hard to keep clean. The first ten models are a joy. Then someone copies a CASE statement into a second model instead of a shared one, a metric gets redefined three different ways, and tests get skipped because the deadline was yesterday. Six months later nobody can answer "which revenue number is right?" without opening four files.
We've seen the same drift across e-commerce, fintech, and agency teams: a dbt project that started as a source of truth and quietly became another place where logic is duplicated and untested. The tool didn't fail. The discipline around it was never put in place.
The fix isn't "rewrite everything." It's a layered model structure (staging, intermediate, marts) that stops logic from being copy-pasted, a semantic layer so one metric has one definition, and tests on every critical model so a bad number blocks the merge instead of reaching a dashboard. dbt was built to do this — most projects just never wire it up.
We implement it the way it should have been built the first time: models mapped to how your business actually reasons, tests and CI that fail loudly, documentation your team can read, and a clean handoff. Tested, documented, yours.
Representative result — logic duplicated across models nobody tests, until no number is trusted.
Test coverage before
0%
After
0%
When dbt makes sense
Pick dbt when…
- You want a single source of truth for business logic
- You need version control and peer review on your models
- You want automated testing on every metric
- Your team already speaks SQL
What we implement
Beyond the tutorial.
01
Project setup
Repo bootstrap, environments, secrets, CI/CD, linting.
02
Model development
Staging, intermediate, and mart layers. Clean dependencies.
03
Testing
Schema tests, data quality tests, and assertions on every critical metric.
04
Documentation
Auto-generated docs, owners, lineage — every column explained.
05
CI/CD
PR-level testing, slim CI runs, production deploys that never surprise anyone.
06
Semantic layer
Metrics defined in one place, consumed by every downstream tool.
In production
What this looks like in production
We don't theorise about model structure and test coverage — we ship it. Two engagements where moving business logic into a disciplined dbt project moved the number that mattered.
Boldspace — creative & PR agency
0×
faster new-client onboarding once business logic lived in dbt instead of forked per-client dashboards
Onboarding fell from 6 weeks to 1 · dbt + BigQuery + Sigma
Netthandelsgruppen — e-commerce
0%
reduction in reporting time after consolidating Shopify, QuickBooks & marketing logic into one dbt project
One source of truth for every metric · dbt + Databricks + Looker
FAQ
Questions we get a lot.
What does a dbt consulting engagement actually include?
A diagnosis first — we read your existing project (or your current transformation setup) for duplicated logic, missing tests, and metrics that don't reconcile. Then implementation: a layered model structure, a semantic layer so each metric has one definition, tests and CI that block bad merges, and documentation. Every engagement ends with a project your team can operate without us.
How is this different from hiring a dbt developer or a big agency?
You work with senior engineers directly — the people doing the modelling, not a rotating bench of juniors. We take fewer clients so each one gets real attention. If your problem is a half-day cleanup, we'll tell you that instead of selling a six-week engagement.
Can you fix our existing dbt project, not just build a new one?
Yes — most of our dbt work is untangling projects that drifted. We refactor the duplicated logic into shared models, add the tests that should have been there, wire up CI, and leave you with documentation. We do it incrementally so nothing breaks while we work.
Do you work with teams outside the US?
Yes. We're based in Mumbai and deliver globally — clients across the US, Europe, and the Middle East. Async-friendly, time-zone aware.
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