The dbt v2 migration policy must protect release momentum without making production compatibility a guess.
Enterprise teams need a clear path off parallel engines, while contributors need evidence before a package result becomes a durable product promise.
Who you’d be doing this for
“My leadership wants a migration date, and I’m still explaining why the same package fails differently each run.”
Indira Rao · Analytics Engineering Lead
Leads a regulated enterprise team migrating a production transformation repository to dbt v2.
What is at stake
Enterprise projects are repeating dbt v2 runs because package failures do not point to one trusted cause. You must weigh migration speed against the evidence required before production teams commit.
Why it isn’t already fixed
Every obvious fix costs something else. That’s the part you’d have to decide.
- migration speed vs production proof
- engine flexibility vs product consistency
- open-source expectations vs enterprise assurance
- automated analysis vs human verification
Why Fivetran
dbt v2 adoption depends on customers trusting that Fusion-powered engine changes preserve governed production workflows.
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.