Goldman Sachs software engineer candidates commonly report an assessment or HireVue before live technical rounds, followed by a Superday-style loop that mixes coding, projects, system design, and behavioral discussion.
$133K
Avg. Base Comp
$170K
Avg. Total Comp
3-5 rounds
Typical Rounds
4-20 weeks
Process Length
Goldman Sachs Software Engineer interviews center on live problem solving and detailed discussion of prior work, although candidates report different entry paths. Some completed a HackerRank or CoderPad assessment, while others received a HireVue-style recorded screen before technical interviews. Prepare for either route rather than assuming one universal sequence.
Coding fluency under explanation is the recurring theme. Supplied questions include arrays, linked lists, hash maps, sorting, two-stack problems, Trapping Rain Water, string compression, and an LRU cache. The practical task is to state an approach, implement it clearly, discuss time and space complexity, and test edge cases while the interviewer follows your reasoning. Several accounts describe multiple technical conversations scheduled together, so maintaining clear communication across successive rounds also matters.
A Superday or final loop may add resume discussion, Java fundamentals, low-level design, or a hiring-manager conversation. Be ready to explain what you built, the obstacles you encountered, and why you made particular technical choices. Behavioral prompts can cover motivation for Goldman Sachs, office choice, team fit, policy judgment, and financial-sector awareness. One candidate was asked how they would handle a critical client request that might violate firm policy.
The exact sequence varies by office and level. A sound preparation plan is to rehearse a concise project walkthrough, practice the reported coding patterns aloud, and structure design answers around requirements, constraints, trade-offs, and complexity. Some accounts describe slow communication after final interviews, so continue other processes and ask recruiting for a concrete decision timeline.
Synthesized from 25 candidate reports by our editorial team.
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Real interview reports from people who went through the Goldman Sachs process.
The system-design portion was the part that stood out most in my process. I applied through the company careers portal and did not have an online assessment. My first interview was a coding round focused on problem-solving and implementation. I was asked questions such as trapping rain water, designing a hash map, and sorting, so the bar felt centered on being able to reason through standard data-structure problems rather than just discuss theory.
The next stage was a Superday with two coding interviews plus resume-based discussion. One interview included a two-stack question, and both interviewers spent time digging into my prior projects, work experience, and technical background. The questions moved quickly, so I found it important to explain my approach clearly as I coded rather than silently work toward an answer.
There was also a final hiring-manager round. It was largely conversational, covering my experience, problem-solving approach, communication, and whether I would be a fit for the team. Overall, the process moved fast and did not drag out. I received an offer but ultimately declined it. My main takeaway is to be ready for a combination of practical coding, a detailed walkthrough of everything on your resume, and concise communication about the tradeoffs behind your approach.
Prep tip from this candidate
Practice coding problems in the style of trapping rain water, hash map design, sorting, and stack-based questions, then rehearse explaining the technical decisions in your past projects since resume deep dives were a major part of the later rounds.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Goldman Sachs
Given a string, write a function to find its first recurring character.
| Question | |
|---|---|
| Find the First Non-Repeating Character in a String | |
| Bagging vs Boosting | |
| Level Of Rain Water In 2D Terrain | |
| Google Maps Improvement | |
| Append Frequency | |
| Cyclic Detection | |
| Minimum Absolute Distance | |
| Target Indices | |
| Cross-Region Inventory Sync | |
| Portfolio Platform Architecture | |
| How Many Friends | |
| Messenger Service Design | |
| Production Model Monitoring | |
| Optimistic vs Pessimistic Locking | |
| Cloud-Agnostic Deployments | |
| SageMaker Deployment Architecture | |
| Impossibly Iterative Fibonacci | |
| Deciding Between Solutions | |
| Alternative Vendor Tradeoff | |
| Client Solution Pushback | |
| LRU Cache 1 | |
| Using APIs for Downstream Tasks | |
| 2nd Highest Salary | |
| Employee Salaries | |
| Merge Sorted Lists | |
| Subscription Overlap | |
| Closest SAT Scores | |
| Empty Neighborhoods | |
| Top Three Salaries |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report HackerRank or CoderPad assessments with coding questions, while some describe HireVue-style recorded prompts on their resume, motivation, and behavioral judgment. Treat either as possible rather than a fixed first stage.
Candidates report live problems involving arrays, linked lists, hash maps, graphs, heaps, trees, and dynamic programming. Explain the approach before coding, discuss complexity, and leave time to write edge-case tests.
Reported Superdays range from two to several interviews and can combine DSA coding, resume deep dives, system design, Java or SQL discussion, and engineering-practice topics. The exact mix appears to vary by team and level.
Candidates report conversations about prior work, communication, why Goldman Sachs, team fit, and scenario-based judgment. Prepare specific examples that connect your technical decisions to outcomes and constraints.
