Revolut Data Engineer candidates report an HR screen, a SQL and Python assessment, live SQL and Python coding, and a hiring-manager conversation. Expect time-pressured SQL across financial-style tables.
$153K
Avg. Base Comp
$185K
Avg. Total Comp
4-5 rounds
Typical Rounds
3-5 weeks
Process Length
Revolut Data Engineer accounts point to a hands-on process centered on SQL and Python. One candidate described five steps: an initial HR conversation, a HackerRank test, live SQL coding, live Python coding, and a hiring-manager round. Because the supplied experiences do not establish a universal sequence, confirm which stages apply to the role before planning preparation around that structure.
For SQL, practice building and explaining queries under time pressure. Candidates report joins across multiple financial-style tables, seven-day moving averages, and year-over-year or month-over-month change analysis. Another live-SQL account described four questions on one schema in 45 minutes, including a triple join and a window-function problem. Speed on multi-table SQL and clear reasoning under follow-up questions are therefore especially relevant.
The SQL round may also test product or business judgment. One candidate described questions that progressed from joins and derived metrics into open-ended plan-launch or fraud scenarios. Before writing a query, clarify the objective, state assumptions, propose suitable metrics, and explain how you would validate the result. Review practical edge cases such as missing records, transaction-state choices, inclusive date windows, integer division, and zero denominators.
Python preparation should remain practical and timed. One reported assessment included counting words and returning unique words in first-seen order, while the same process included a separate live Python stage. Practice implementing small transformations cleanly, testing basic edge cases, and narrating your approach rather than working silently. End-to-end duration was not reported in the supplied experiences.
Synthesized from 7 candidate reports by our editorial team.
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Real interview reports from people who went through the Revolut process.
I first had an interview with HR. The interviewer was very kind and put me at ease. We talked about the process, which had five steps: an initial HR conversation, a HackerRank test, SQL live coding, Python live coding, and a hiring manager round.
Questions asked: The HackerRank had SQL and Python exercises. The SQL exercises asked me to calculate a moving average over the last seven days. The Python exercises were basic, including counting how many times a word appears in a string and getting the unique words while preserving the order in which they first appear.
The third round consisted of live SQL questions. The exercises involved financial tables and joins across multiple tables. The interviewer asked me to compute rolling averages and identify users who had an increase of a certain percentage year over year and month over month.
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Topics based on recent interview experiences.
Featured question at Revolut
Write a query that returns all neighborhoods that have 0 users.
| Question | |
|---|---|
| Rolling Bank Transactions | |
| Top Three Salaries | |
| Experiment Validity | |
| Last Transaction | |
| Like Tracker | |
| Month Over Month | |
| Daily Logins | |
| Top 3 Users | |
| Third Purchase | |
| Rolling Average Steps | |
| Total Spent on Products | |
| Find the First Non-Repeating Character in a String | |
| Daily Retention Summary | |
| Post Composer Drop | |
| Cumulative Reset | |
| Size of Joins | |
| Google Maps Improvement | |
| Subscription Retention | |
| Sort Strings | |
| Hurdles In Data Projects | |
| Word Frequency | |
| Duplicate Rows | |
| Count Transactions | |
| Payments Received | |
| Time on FB Distribution | |
| Slow SQL Query | |
| Optimistic vs Pessimistic Locking | |
| Success Measurement | |
| Assumptions of Linear Regression |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report an initial HR or recruiter conversation that covers background and the process. Prepare a concise account of your data-engineering experience and the projects you can discuss clearly.
One Data Engineer candidate reported a HackerRank test with SQL and Python exercises, including a seven-day moving average and basic string tasks. Another account reported a timed coding assessment before live interviews.
Candidates report live SQL questions involving joins across multiple tables, rolling averages, and period-over-period user changes. One report describes four questions on one schema within 45 minutes, including a triple join and a window function.
A Data Engineer candidate reported a separate live Python coding stage. Another candidate’s reported Python task was an in-memory URL shortener that returned consistent short codes, handled invalid codes, and included core tests.
One candidate described a hiring-manager round after the coding stages. Candidates also report business or product discussion in a SQL-focused interview, so you may be asked to explain assumptions and your reasoning.
