Data Quality Monitoring System
Build automated data quality monitoring with Great Expectations or dbt tests. Catch data bugs before stakeholders do.
Great Expectations or dbt testsPythonSlack or PagerDuty integration
About this project
Data quality is the most underrated specialty in data engineering. This project teaches the methodology: defining expectations (uniqueness, freshness, distribution checks), automating them, alerting on failures, and the org skill of getting other teams to care. Pick an existing data pipeline (yours or open-source) and add comprehensive data tests.
Why build this in 2026?
AI products break loudly when training/inference data shifts. Data quality is now business-critical.
What you'll ship
- GitHub repo
Documented test suite (20+ expectations)
Slack/email alert configured
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Skills you'll practice
sqlpythondata modeling