Top 4 Customer data integration Interview Questions
Browse 4 real-world technical and behavioral interview questions about Customer data integration. Review scenarios, edge cases, and architectural best practices.
You get a messy customer export and three hours to turn it into something they can use. What do you build first?
Build the data profile and a validation report first, not the dashboard. Read every column as text, infer types from evidence, show the customer what you found within the first hour, then load accepted rows idempotently into a staging table with a rejected-rows file that explains every exclusion.
You have read access to the customer's production database and there is no staging environment. How do you develop and test without putting their system at risk?
Pull a bounded, representative extract into an environment you control and develop against that, keeping production for read-only verification under agreed limits, and treat every write path as something proven against a restored copy before it runs anywhere near live.
The customer's schema has no documentation and the person who designed it has left. How do you work out what the tables actually mean?
Read the data rather than the DDL: profile every column for cardinality, null rate and value distribution, use foreign-key-shaped joins to test relationships you suspect, and confirm each conclusion against a report the business already trusts before you build on it.
The business told you a field is always populated, and in production it is null for a third of the rows. How do you work out what is going on and what do you do about it?
Segment the nulls before drawing any conclusion — by date, source system, record type and creating process — because a null rate that clusters is a documented business path nobody mentioned, while one spread evenly is usually a genuine capture defect.