
Mercury Software Engineer interview typically runs 2 rounds: SQL schema PR review, AI-assisted coding round. It took about 3 hours and felt highly technical with a debrief.
$105K
Avg. Base Comp
$171K
Avg. Total Comp
2-3
Typical Rounds
1-2 weeks
Process Length
We've seen Mercury lean hard into real-world engineering judgment rather than abstract algorithm drills. In the candidate experience we reviewed, the opening schema PR review set the tone: the company appears to care about whether you can reason through database design tradeoffs, spot issues in a proposed change, and explain why a schema is or isn’t resilient. That’s a strong signal that Mercury values engineers who think like owners of production systems, not just implementers of tickets.
A recurring theme is the emphasis on how you work with modern tools. The AI-assisted coding round wasn’t treated as a novelty; it was part of the evaluation, and the debrief suggests they were watching how candidates used AI, validated outputs, and made decisions under that workflow. For us, that points to a company that wants engineers who can stay sharp while using AI productively, without outsourcing judgment. The practical takeaway is that Mercury seems to reward candidates who can articulate tradeoffs clearly, defend design choices, and show they understand the operational consequences of their code.
Synthetized from 1 candidates reports by our editorial team.
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Featured question at Mercury
Select the 2nd highest salary in the engineering department
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| Empty Neighborhoods | |
| Top Three Salaries | |
| Merge Sorted Lists | |
| Subscription Overlap | |
| Rolling Bank Transactions | |
| Customer Orders | |
| Comments Histogram | |
| String Shift | |
| Random SQL Sample | |
| Closest SAT Scores | |
| Prime to N | |
| Upsell Transactions | |
| Monthly Customer Report | |
| Over 100 Dollars | |
| First Touch Attribution | |
| Raining in Seattle | |
| Scrambled Tickets | |
| Hurdles In Data Projects | |
| P-value to a Layman | |
| Google Maps Improvement | |
| Last Transaction | |
| Size of Joins | |
| Minimum Change | |
| Address Schema | |
| Top 3 Users | |
| Download Facts | |
| Permutation Palindrome | |
| Top 5 Turnover Risk | |
| Delivery Estimate Model |
Synthesized from candidate reports. Individual experiences may vary.
The process begins with a review of an SQL schema pull request. Candidates are expected to discuss database design fundamentals and make practical engineering judgments about schema structure and tradeoffs.
The second round is a long coding session focused on building with AI tools. It emphasizes practical implementation skills, engineering judgment, and how well you can work through problems with AI assistance.
At the end of the coding round, there is a debrief where the interviewer and candidate discuss the approach, decisions made, and overall performance.