Two-part question which tripped me up a bit.
Break the problem into two parts: first, calculate each employee's total net pay for Q1 2023 by aggregating payroll transactions; second, use a window function to rank pay periods per employee and compute the percentage change between the two most recent periods, then filter for negative changes. Ensure you handle date filtering correctly and consider employees with fewer than two pay periods.
Pro tip: Clarify the definition of 'net pay' and 'pay period' upfront—at Gusto, pay periods may vary by employee, so confirm whether to use transaction dates or period end dates. Also, mention that you'd validate results by checking edge cases like employees with only one pay period.
Identify the relevant columns in the employees and payroll transactions tables, and confirm how net pay is calculated (gross minus deductions). Clarify what constitutes a 'pay period' and how to identify the two most recent ones.
Filter payroll transactions to Q1 2023 (January 1 to March 31) and sum gross and deductions per employee to compute total net pay for the quarter.
Use a window function like ROW_NUMBER() or RANK() partitioned by employee and ordered by pay period date descending to identify the two most recent pay periods. Then compute the percentage change in net pay between them.
Filter to employees whose net pay decreased (percentage change < 0) and join back to the employees table to include relevant employee information.
Consider employees with fewer than two pay periods (exclude them or handle separately) and ensure date ranges are correctly applied. Validate results with sample data or sanity checks.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.