Interview Guides
Complex analytics queries are common when working with Demandbase account, campaign, and engagement data. Poorly structured joins and aggregations can cause large scans, duplicate amplification, and slow dashboards.
Explain how you would optimize a complex PostgreSQL query that joins several Demandbase-style fact and dimension tables and computes aggregated metrics. You should discuss how you would identify bottlenecks, reduce unnecessary row expansion before aggregation, decide when to use CTEs or window functions, and choose indexes that support the query shape.
The interviewer expects a practical database answer, not generic advice. Focus on join order, pre-aggregation, filtering strategy, execution plans, cardinality, and PostgreSQL-specific tradeoffs such as materialization behavior, hash vs merge joins, and index usefulness for grouped workloads.
