Wise moves money across borders. Practice country-level aggregation, fee math, period-over-period growth and transfer recency on a synthetic card-transaction ledger and the app’s ecommerce tables, with an AI tutor when you get stuck.
16 challenges
Wise-pattern set
Runnable data
Orders + a card ledger
AI tutor
Step-by-step hints
What this page is: we have no dated public source for how Wise runs its SQL round, so this page does not state one — no duration, no platform, no stage list. What follows is general SQL interview practice on the kind of data Wise works with. What is ours: the questions are SQL Quest challenges and the topic emphasis is our editorial judgement, not a measured breakdown of Wise's interview. Pages with dated sources say so in this spot.
The 16 challenges tagged Wise in the SQL Quest bank, with every raw challenge tag resolved to the 9 canonical skills. Each share is the portion of those 16 challenges that exercise the skill — a challenge exercises several, so the shares do not sum to 100%. This is the composition of the practice set on this page, not a measurement of Wise’s interview.
These are SQL Quest challenges chosen because their SQL matches the work — Querying Basics, Aggregation & Grouping, Date Functions. They are not questions Wise has asked, and this page does not claim to know its questions. All of the six play free; each card opens the challenge itself.
General guidance about analytics SQL work — not sourced from Wise and not a description of its process. We have no dated, citable source for how Wise runs its SQL round, so this page states none.
Skillmap
Ten questions, no signup. You get a readiness score weighted to the SQL this page covers, your Skillmap across joins, window functions, aggregation and the rest, and the weakest skill to practise first.
Drill the skills the Wise set leans on, one at a time: GROUP BY exercises · Date function practice · JOIN practice · CTE practice · CASE WHEN practice — or browse every SQL practice question.
Every question in the Wise set, one page each with the schema and a hint: Country Codes in Uppercase · Monthly Spend Per Account · Card Spend by Country · The Ledger's First Week, Day by Day · Pivot: Order Status by Country · Customer Recency Analysis · Multi-Month Active Customers · Month-over-Month Customer Growth · Customer Signup Quarter (Date + CASE) · Country × Category Coverage Matrix (Cross Join) · Membership × Country Activity (Cross Join) · Month-over-Month Spend Growth by Category · How Long Has Each Card Been Active? · Top Spender Per Country · Month-over-Month Revenue Growth · Cards That Never Spend at Home.
No signup required. No credit card. Open the app and start practicing Wise-pattern SQL right now.
Launch SQL Quest — It's Free ⚡Works on Chrome, Firefox, Safari, Edge · No plugins · No downloads
Preparing for the analytics round? Read SQL for fraud analytics — velocity checks, rolling windows and self-joins, with a self-check quiz that drops you into real banking data.
Interviewing at more than one company? The same patterns carry: Stripe · Revolut · Plaid · Ramp — or the full company-by-company interview guide.