Welcome to your interview.
The question is on your right: Optimize Large PostgreSQL Query Performance. Take a moment with it first.
Talk your thinking through with me if you like - when you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes). Discussion and graded submissions share your five interviewer interactions, so spend them well.
Slow queries on large tables are a common issue in analytics environments, especially when dashboards and recurring TEKsystems reporting workloads depend on them. Interviewers want to hear how you diagnose the bottleneck, not just a list of generic tuning ideas.
You are asked how you would optimize a slow-running PostgreSQL query against a table with millions of rows. Explain how you would investigate the problem, what you would look for in the execution plan, how you would decide whether indexing helps, and when you would consider rewriting joins, filters, aggregations, or using partitioning. You should also explain how data distribution, stale statistics, and selecting unnecessary columns can affect performance.
A strong answer should cover both diagnosis and remediation. The interviewer is typically looking for a practical, ordered approach grounded in PostgreSQL behavior rather than vague advice like "add an index" or "use a CTE."