• Row count vs yesterday (alert on >30% change)

Reyansh Iyer

Data Engineer | Spark, Airflow, dbt, Snowflake | Pipelines that don't break on Mondays

8 Oct 2026 Data Engineering Guild

• Row count vs yesterday (alert on >30% change) • Null rate on key columns • Uniqueness of primary keys • Freshness (max updated_at) • Referential checks for critical joins Catches 90% of issues before anyone opens a dashboard.

5 reactions2 comments

Comments

AV
Anika Verma8 Oct 2026
The row-count-vs-yesterday check alone would have saved me from 2 embarrassing dashboards 😅
PB
Priya Banerjee8 Oct 2026
Adding freshness checks this week.

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