SQL & Data Modeling interview questions

Rank orders per customer and return each customer's second largest order.

Window Functions · sql · medium · 12 min

Build a three-step funnel from an events table with conversion rates.

Funnels & Sessions · sql · hard · 18 min

Pick the right grain for an order-line fact table.

Schema Design · multiple choice · easy · 6 min

From the orders table, return each order_date with that day's revenue and a cumulative running total of revenue through that date, ordered by date.

Window Functions · sql · medium · 10 min

From an events table, for each calendar date return the number of DISTINCT users active in the trailing 7 days (that date and the 6 days before it).

Window Functions · sql · hard · 15 min

Return each month, its revenue, and the month-over-month growth as a percentage rounded to one decimal.

Window Functions · sql · medium · 10 min

Return the top 3 products by total revenue within each category.

Window Functions · sql · medium · 12 min

Each row is one calendar day a user logged in (no duplicates).

Gaps & Islands · sql · hard · 18 min

Assign a session id to each event per user, starting a new session whenever the gap since the user's previous event exceeds 30 minutes.

Sessionization · sql · hard · 18 min

The snapshots table has multiple rows per listing.

Deduplication · sql · medium · 10 min

For each signup date cohort, return the cohort size and the Day-7 retention rate: the share of users who were active exactly 7 days after signup.

Cohort Retention · sql · hard · 18 min

Return the median order amount for each customer segment.

Aggregation · sql · medium · 8 min

Count the distinct users who VIEWED a product and later PURCHASED that same product (purchase time strictly after the view).

Self Joins · sql · medium · 12 min

Return one row per category with three columns of revenue: Jan, Feb, and Mar 2026.

Pivoting · sql · medium · 10 min

You maintain a customer dimension.

Schema Design · multiple choice · medium · 6 min

For each user, return the length of their longest streak of consecutive calendar months with at least one activity.

Window Functions · sql · medium · 18 min

Create sessions separately for each user.

Funnels & Sessions · sql · hard · 25 min

Group users by Monday-starting signup week.

Funnels & Sessions · sql · medium · 20 min

Each plan_history row starts a new plan period for an account and remains effective until the next change.

Schema Design · sql · hard · 22 min

For every calendar date from the first through last order date, compute the trailing seven-calendar-day cancellation rate: canceled orders divided by all orders in that date and the prior six dates.

Window Functions · sql · hard · 22 min