DATA OPS
Snowflake Schema Drift Sentinel with Linear Remediation
Snapshots Snowflake table contracts on a schedule, diffs them against the last known-good baseline.
How it runs
The automated pipeline, trigger to output.
- TriggerDaily schedule fires
- ActionRead current table contracts from Snowflake INFORMATION_SCHEMASnowflake
- LogicDiff against stored baseline; classify breaking vs additive
- LogicStop if no breaking drift detected
- OutputOpen a Linear issue per breaking changeLinear
- ActionPersist new contracts as next baselineSnowflake
What it does
This workflow takes a daily fingerprint of your governed Snowflake tables — column names, data types, nullability, and primary keys — and compares it to the baseline captured on the previous run. When a contract changes (a column dropped, a type narrowed, a NOT NULL added), it files a structured Linear issue describing exactly what moved and which downstream models depend on it.
When to use it
Use it when analytics or reverse-ETL pipelines keep silently breaking because someone altered a source table without telling the data team. It turns invisible, after-the-fact failures into a tracked remediation task the moment drift appears.
How it works
- 1A daily schedule fires the run.
- 2Query `INFORMATION_SCHEMA` in Snowflake for the current column contracts of the watched tables.
- 3Compare each table's contract against the stored baseline and classify changes as breaking or additive.
- 4If no breaking change is found, exit quietly and refresh the baseline.
- 5For each breaking change, create a Linear issue with the table, the diff, and severity label.
- 6Persist the new contracts as the next baseline.
Set it up
What you configure once, before turning it on.
- 1Connect SnowflakeWarehouses, queries, shares.
- 2Connect LinearIssues, projects, cycles, triage.
- 3Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 4Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 5Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
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