How Do You Ensure Data Quality?

Data SLOs, Cost-of-Error Analysis, and Quality Regression At intermediate, quality gates are pass/fail. The interviewer wants to hear you talk about SLOs and cost models. The trap is saying 'we check for nulls.' The senior signal is: 'We defined a completeness SLO of 99.95% for revenue-critical tables, with a cost model that estimates $12K per hour of underreported revenue, which determines our alerting threshold and on-call response time.' A Data SLO is a measurable quality target: 'fewer than 0.01% orphaned customer_ids per day' or 'revenue figures accurate within 0.1% of the source system.' SLOs give you a shared language with stakeholders and a threshold for when to page vs. when to ticket. The interviewer wants to hear that you've negotiated SLOs with business partners, not just set a