DATA OPS

BigQuery schema-contract gate on GitHub PRs

On every pull request touching schema definitions, compares the proposed table shape against the live BigQuery schema and the declared data contract.

CategoryData Ops
Enginesim
Difficultyadvanced
Triggerevent
Steps4
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerGitHub pull request touches schema filesGitHubGitHub
  • ActionRead live table schema from BigQueryGoogle BigQueryBigQuery
  • LogicDiff proposed vs. live; check contract declaration
  • OutputComment verdict and set blocking commit status on GitHubGitHubGitHub

What it does

Shifts schema-drift detection left into code review. When a PR proposes changes to a BigQuery table's DDL or schema file, it diffs the proposed shape against both production and the registered data contract, and posts a verdict comment that gates the merge.

When to use it

Use it when schema changes flow through version control and you want breaking changes declared and reviewed rather than discovered in production. It turns the data contract into an enforced check instead of a wiki page.

How it works

  1. 1A GitHub pull-request event triggers the flow when schema files change.
  2. 2The flow reads the proposed schema from the PR and the current live schema from BigQuery.
  3. 3A logic step computes the diff and checks whether any breaking change was declared in the PR's contract annotation.
  4. 4If the change is purely additive or properly declared, it posts a passing status comment.
  5. 5If an undeclared breaking change is found, it posts a failing comment listing the offending columns and sets a blocking commit status on GitHub.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GitHubRepos, issues, pull requests, actions.
  2. 2
    Connect BigQueryDatasets, queries, schemas.
  3. 3
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  4. 4
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  5. 5
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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