
UBS Software Engineer interview typically runs 2 rounds: online assessment and technical/behavioral interview. Timeline is about 1-2 weeks, with a structured, role-specific process.
$127K
Avg. Base Comp
$161K
Avg. Total Comp
2-5
Typical Rounds
2-6 weeks
Process Length
We've seen UBS evaluate software engineers less like pure algorithm candidates and more like practitioners who can explain how they build, ship, and troubleshoot real systems. Multiple candidates reported that the strongest signal was not a clever trick answer, but whether they could walk through their own projects with confidence — from Terraform and CI/CD to Azure, AKS, React basics, and deployment choices. That lines up with a recurring theme in the experiences: resume credibility matters, and interviewers quickly probe whether the work listed on paper matches what you can defend live.
A second pattern is UBS’s preference for structured judgment over open-ended coding marathons. Our candidates report a mix of situational judgment, cognitive, and personality-style assessments alongside technical screens, and even the technical questions often stay grounded in practical decision-making: what database to choose, how to handle an error, or how to reason through a pipeline setup. The non-obvious part is that they seem to care a lot about clarity under constraints — especially in timed or rigid formats where you have little room to ramble. Candidates who did well were the ones who could stay precise, explain tradeoffs, and show they understood the why behind their choices, not just the syntax.
Synthetized from 3 candidates reports by our editorial team.
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Real interview reports from people who went through the Ubs process.
The process was pretty straightforward, but it felt broader than a pure coding screen. I had two rounds in total. The first was a HackerRank-style technical test, and the exact content seemed to depend on the role. In my case, it covered Java plus SQL, and the other version I saw for the same process was full-stack Java with React. The questions weren’t especially deep algorithmically, but they did require careful reading and attention to detail. There was also a numerical/pattern-recognition section, so I had to slow down and actually observe each question instead of rushing through it. Alongside that, there was a personality-style assessment with scenario questions where you pick the most suitable action, plus a company culture/logical understanding test that felt very situational.
The second round was on Teams and was more technical discussion than coding challenge. They focused on low-level design implementation, and in another interview I saw for the same role, the conversation also included Java basics, Spring Boot, design patterns, computer science fundamentals, and a walkthrough of projects on the resume. My own questions were similar in spirit: self-introduction, why I chose my college, hobbies, what backend and frontend technologies I’d use, what database I’d pick, and how I’d handle an error if it occurred. The interviewers were two people, and the whole thing lasted about 30 minutes. Overall, the process felt more like a mix of technical screening and fit/culture checks than a heavy coding interview. I didn’t get an offer, and the most important takeaway for me was to prepare for role-specific technical basics, low-level design, and those situational judgment tests rather than only grinding algorithms.
Prep tip from this candidate
Be ready for a HackerRank-style screen that can shift between Java+SQL and full-stack Java+React, and don’t ignore the numerical/pattern-recognition and situational judgment sections. For the Teams round, review Java basics, Spring Boot, design patterns, and be able to explain a low-level design approach plus the technologies and database you’d choose for a simple backend/frontend setup.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Ubs
Strategically resolving misaligned expectations with stakeholders for a successful project outcome
| Question | |
|---|---|
| Your Strengths and Weaknesses | |
| Statistically Significant Test | |
| 2nd Highest Salary | |
| Employee Salaries | |
| Bagging vs Boosting | |
| Random SQL Sample | |
| P-value to a Layman | |
| Size of Joins | |
| Hurdles In Data Projects | |
| Cyclic Detection | |
| Three Zebras | |
| Target Indices | |
| Duplicate Rows | |
| Type I and II Errors | |
| Modifying a Billion Rows | |
| Same Characters | |
| Swap Variables | |
| Integer String Addition | |
| Triangle as Binary Array | |
| Why Do You Want to Work With Us | |
| Drink Production Allocation | |
| Blob Indexing | |
| International e-Commerce Warehouse | |
| Client Solution Pushback | |
| Justify a Neural Network | |
| Processing Large CSV | |
| Kindergarten Feasibility | |
| Google Earth Storage | |
| Branch Sales Pivot |
Synthesized from candidate reports. Individual experiences may vary.
Candidates first complete a HackerRank-style online assessment. Depending on the role, it may include Java and SQL or full-stack Java with React, along with numerical or pattern-recognition questions and situational personality/culture judgment items.
A rigid HireVue-style interview follows, with short preparation time and timed responses. Questions are mostly behavioral and situational, such as introducing yourself, explaining clean code, and discussing a technology topic in the news.
The next round is a live technical discussion, often over Teams or as part of an assessment center. Interviewers focus on low-level design, Java basics, Spring Boot, design patterns, computer science fundamentals, and a walkthrough of projects and resume experience.
Some candidates continue to an assessment center with multiple interviews, including a technical interview, a group case study, and one-on-one behavioral conversations. This stage can also include coding questions, logic or puzzle-style problem solving, and competency or statistics questions.
The final stage is a managerial or HR-style conversation focused on fit, working style, and broader engineering judgment. Candidates may be asked about their projects, debugging approach, performance optimization, accessibility testing, and basic frontend concepts like React props and state before a final decision is made.