DATA OPS
Snowflake schema-drift sentinel to Linear
Snapshots a Snowflake table's column shape on a schedule, compares it to the last known shape, and opens a Linear ticket the moment a column is added, dropped, or retyped.
How it runs
The automated pipeline, trigger to output.
- TriggerDaily schedule fires
- ActionQuery Snowflake INFORMATION_SCHEMA for column shapeSnowflake
- LogicDiff current fingerprint vs. stored baseline
- ActionOpen Linear ticket with column diffLinear
- ActionPersist new fingerprint as baselinePostgres
What it does
Watches one or more Snowflake source tables for structural change — new columns, removed columns, or altered data types — and files a remediation ticket in Linear with the exact diff so a data engineer can act before downstream models break.
When to use it
Use it when an upstream team owns a table you depend on and ships schema changes without warning. Catching the drift the morning it lands beats discovering it through a failed dbt run or a silently null dashboard.
How it works
- 1A schedule fires each morning and queries `INFORMATION_SCHEMA.COLUMNS` in Snowflake for the watched table.
- 2The current column-name-and-type fingerprint is compared against the snapshot persisted from the previous run.
- 3A logic step branches: if the fingerprint is unchanged, the run ends quietly; if it differs, it computes the added, dropped, and retyped columns.
- 4A Linear issue is created on the data-platform team, titled with the table name and tagged `schema-drift`, with the column-level diff in the body.
- 5The new fingerprint is written back to storage as the baseline for the next run.
Set it up
What you configure once, before turning it on.
- 1Connect SnowflakeWarehouses, queries, shares.
- 2Connect LinearIssues, projects, cycles, triage.
- 3Connect PostgresAny Postgres URL — query, write, migrate.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, 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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