Fast answers to failed runs compete with the evidence needed to trust them.
The investigation workflow must shorten on-call diagnosis without turning an unverified AI explanation into the incident record.
Who you’d be doing this for
“My finance dashboard missed the morning handoff, and I still don’t know what failed first.”
Petr Munteanu · Analytics Engineer
Owns production dbt models whose downstream reporting depends on scheduled runs completing predictably.
What is at stake
Failed scheduled runs are taking engineers through several systems before they can name a cause. You must decide what evidence AI can assemble and what an engineer must confirm.
Why it isn’t already fixed
Every obvious fix costs something else. That’s the part you’d have to decide.
- faster diagnosis vs. evidence-backed confidence
- on-call speed vs. engineer confirmation
- broad failure coverage vs. bounded pilot scope
- AI drafting vs. operational accountability
Why Fivetran
The scheduler, execution harness, and results processing are the control plane behind customer dbt runs.
Written with these in mind
Not your kind of problem? 43 more at Fivetran, or browse every organization.
This is the setup. The work is inside.
Running it puts you in the room: the full situation and its constraints, stakeholders who push back in their own words, and the decisions that are yours to make. What you produce becomes a Day One Plan — work you can show someone instead of describing.