Data engineering that fails loudly instead of silently
Fewer nightly failures, a smaller warehouse bill, and reports reconciled against the source of truth, so a quiet disagreement never costs you a decision.
Sounds familiar?
- The nightly job fails on a different model every night, and raising the timeout never fixes it.
- The warehouse bill keeps growing and nobody can say why.
- The dashboard shows one number and the ad account another, and nobody knows which is right.
- A connector silently stopped, and the report showed zero.
What you get
- A review of your pipelines and warehouse that measures where cost and failures actually come from
- Structural fixes, verified by comparing values, not just row counts
- A daily reconciliation between your source of truth and your reports, including silent failures
- Alerts that name the failing file or row, so the fix starts at the cause
Proof it works
Real engagements, with the clients anonymized.
Cut a nightly BigQuery scan by 95%
Two months of raising the timeout hadn't fixed the failures. The real cause was unpartitioned sources scanning the full history every night.
Caught a doubled ad spend line and an $11B phantom revenue bug
A daily reconciler between the ad accounts and the warehouse, built to catch silent failures, not just mismatches.
Price and timeline
Works with your stack
The method stays the same; the connector changes.
Questions
Do you only work with BigQuery and dbt?
Our case work is on BigQuery and dbt. On another warehouse the diagnostic method carries over, and we'll tell you honestly where our experience is thinner.
Why didn't raising the timeout fix our failing job?
Usually the timeout is a symptom. In our case study nothing was partitioned, so every model rescanned the full history each night and heavy models competed for slots. Measuring the scan per model showed the real cause.
How do you know a fix didn't change the data?
We compare values, not only row counts, and diff the compiled SQL before and after every change.
What is a reconciler?
A daily check that compares what the source system says against what your report says, per entity, and alerts on any disagreement. It includes the case where both sides show zero, which a simple total would read as healthy.
Keep reading
Other services
Want to see where you'd land?
Tell us what hurts and we'll say honestly whether we're the right fit, and what it would cost.