Good, went well, explained about project details, Python coding, SQL coding, testing , sprint details : How do you validate large volume data loads in ETL testing? A: I use a combination of row count checks, data profiling, and aggregate comparisons. For large datasets, I run SQL queries to check sum, count, min, max on numeric columns to ensure source and target consistency. I also perform sampling and use automation scripts in Python for record-by-record validation if needed.