dbt Repo Performance
Cut dbt runtimes in half. Or better.
We audit every model, rewrite slow ones with incremental + microbatch strategies, prune unused exposures, and turn 4-hour runs into 40-minute runs.
The work
Slow dbt runs are rarely about Snowflake or BigQuery — they're about repo shape. Wide select-stars, materializations chosen by habit, missing incremental keys, stale exposures fan-out into a graph that runs for hours. We do the deep work most teams don't have the time for.
Outcomes
- Median model runtime cut 40–70%
- Critical path identified and shortened
- Compute spend reduced (Snowflake credits, BigQuery slot-hours)
- Stale models and exposures retired
- A repo your team can understand in a week, not a quarter
What you get
- Performance audit report (top 50 expensive models, recommendations)
- Refactored incremental + microbatch models for hot paths
- Tag strategy + selector-based scheduling
- Pre-commit + CI checks that prevent regressions
- Cost dashboard you actually look at
Start a conversation
Tell us what's slowing your data team down.
We maintain a small client roster on purpose. If we're the wrong fit, we'll say so — and usually we know somebody who isn't.
- Replies within 2 business days
- NDA before specifics
- Fixed-scope first engagement, retainer if it works