DATA OPS

Schema-Drift Triage Agent that Maps Impact and Files a Linear Issue

When BigQuery schema drift is detected, an agent traces which downstream models, dashboards, and pipelines depend on the changed column, writes a plain-English impact assessment.

CategoryData Ops
Enginepaperclip
Difficultyadvanced
Triggerwebhook
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDrift-detected webhook receivedHTTP webhook
  • ActionTrace dependent models and jobs via BigQuery lineageGoogle BigQueryBigQuery
  • LogicAgent assesses blast radius and assigns severity
  • ActionPost impact summary to SlackSlack
  • OutputOpen prioritized Linear issue for the ownerLinearLinear

What it does

This goes beyond detection to triage. Once drift is found on a watched BigQuery table, an agent walks the dependency lineage to determine what actually breaks — which transformed models reference the column, which dashboards surface it, which jobs will fail. It drafts a human-readable impact summary, picks a severity, and files a Linear issue assigned to the owning team with the diff and a suggested fix.

When to use it

Use it when raw drift alerts create more triage work than they save. The agent does the reasoning a data engineer would otherwise do by hand: scoping blast radius and routing the ticket to whoever owns the affected assets.

How it works

  1. 1A schema-drift webhook from the detector fires with the changed table and column.
  2. 2The agent queries BigQuery lineage and metadata to find dependent models, views, and jobs.
  3. 3The agent reasons over the blast radius and writes an impact assessment with a severity.
  4. 4It posts the summary to Slack for visibility.
  5. 5It opens a Linear issue with the diff, impact, owner, and suggested remediation.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect BigQueryDatasets, queries, schemas.
  3. 3
    Connect LinearIssues, projects, cycles, triage.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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