Q1
Walk me through how you would design a data pipeline to process 500GB of daily transactional data, extract key metrics, and load them into a data warehouse. What tools would you use and why?
Why they ask this:* They want to assess your understanding of ETL/ELT processes, scalability considerations, and your familiarity with modern data stack tools (SQL, Python, Apache Spark, cloud platforms, etc.).
Q2
Explain the difference between INNER JOIN, LEFT JOIN, and FULL OUTER JOIN with a real-world example relevant to business analytics. When would you use each?
Why they ask this:* This tests foundational SQL knowledge and your ability to think about data relationships, which is critical for accurate analysis and avoiding data loss in joins.
Q3
You have a dataset with 10 million rows and need to identify outliers in customer spending. Walk through your approach, including statistical methods you'd use and how you'd handle edge cases.
Why they ask this:* They're evaluating your statistical reasoning, knowledge of outlier detection techniques (z-score, IQR, isolation forests), and practical problem-solving skills with large datasets.
Q4
Describe a time you had to optimize a slow SQL query that was taking 15 minutes to run. What techniques did you use to diagnose and improve performance?