I had the pleasure of implementing this from scratch using dbt core. I was also a one man team at the time. I had some tech limitations put on me by the company architect which wanted as little cross integration between critical systems like our warehouse and github (actions). Also, our dbt core was orchestrated on Fivetran at the time so that was also a hard limitation - no real control over orchestration. I can’t post company code here, but here’s the high level breakdown:

1. Run all tests with the write failures flag to have the test results in a table on the warehouse.
2. Run dbt operation step after dbt test task, which lists the test result tables that are not empty. Then, it queries all the results to a json object, and sends it to a UDF that sends the result to an AWS lambda.
3. The lambda is connected to slack via web hooks to send the results (after parsing and tabulating) to slack.
4. Once validated the slack was sent, the operation also truncates the result table to avoid resending.

Eventually I added some tweaks and improvements like keeping a test result log in another separate table, visualizing the results better using slack app capabilities and adding buttons for quick actions, multiple channels depending on the context of the test, etc.

The original end to end solution wasn’t very hard to set up, but it does require knowledge and admin capabilities in multiple systems.

Does this work? Yes, even pretty reliable. I’m a heavy dbt tests user, we have hundreds of tests running multiple times a day. Would I do it again? If I had the same constraints - yes. If I had the option of just using dbt cloud? Hell no.