Most Common Interview Questions Asked at Big Firms – Google, Microsoft, Goldman Sachs, Morgan Stanley, and JP Morgan

TL;DR

• Tech giants (Google, Microsoft) lean on algorithmic depth, system design, and cultural fit.
• Finance powerhouses (Goldman Sachs, Morgan Stanley, JP Morgan) blend quantitative rigor with market fluency and pressure-tested judgment.
• AI-driven platforms now score both technical and behavioral responses, so practice in realistic, timed environments.
• Evergreen preparation mix: pattern-based DSA practice, structured STAR stories, mock interviews, and daily market/product research.
• Geo-aware strategy: align your examples with target offices (US, UK, India, APAC) and understand local hiring timelines.

Voice search snippet: The most common Google, Microsoft, Goldman Sachs, Morgan Stanley, and JP Morgan interview questions revolve around STAR-format leadership stories, mid-level DSA patterns, HireVue-style behavioral clips, and real-world case studies that prove you can analyze markets, ship scalable systems, and stay composed under pressure.

How to Use This Guide

• Need quick prep? Jump to each company’s Quick Answer subsection for the top three hiring signals interviewers listen for.
• Building a roadmap? Use the Preparation Playbook tables plus our ATS resume optimization checklist and complete job preparation guide to stack-rank tasks.
• Optimizing for voice search and AI answers? Copy the question-style subheadings as flashcards and rehearse concise, 20-second spoken responses.
• Targeting specific regions? Match the country insights in Geo-Aware Preparation Tips with local meetups, hiring timelines, and visa rules.

Interview Landscape at Top Firms

Landing an offer at Google, Microsoft, Goldman Sachs, Morgan Stanley, or JP Morgan demands more than raw technical skill. Each company runs a multi-stage evaluation that combines behavioral screens, hands-on technical drills, and real-world case scenarios. Tech firms tilt toward algorithms, system design, and collaborative problem-solving, while finance firms balance coding or modeling fundamentals with market awareness and client-ready communication.

Both sectors increasingly rely on AI-assisted assessments, collaborative coding environments, and scenario-based prompts that replicate day-to-day work. Hiring standards have tightened, so strong candidates arrive with polished narratives, repeatable problem-solving frameworks, and the ability to communicate clearly under pressure.

Google: Where Logic Meets Innovation

Behavioral Focus

Google screens for “Googleyness”—curiosity, ethics, teamwork, and emergent leadership. Expect STAR-format prompts such as:

• Describe a time you influenced without formal authority.
• Share an instance where new data forced you to change course.
• Explain a conflict you resolved and what you learned.
• Walk through your favorite Google product and propose an improvement.
• Highlight a moment when you built something from scratch.

Patterns to highlight: comfort with ambiguity, learning from failure, inclusive collaboration, and a bias for action.

Quick Answer: What Does Google Interview For?

Google interviewers listen for candidates who can frame ambiguous problems, compose optimal code on the whiteboard or shared doc without syntax help, and back up decisions with clear trade-off narratives. Expect at least one direct question about impact at scale and another asking how you learn from failure.

Technical Expectations

Coding interviews emphasize clean, optimal solutions across arrays, strings, trees, graphs, and dynamic programming. Frequent topics include:

• Two-pointer and sliding window patterns (longest substring, two-sum variants)
• Linked list manipulation (reverse list, detect cycle, merge sorted lists)
• Graph/DFS/BFS challenges (number of islands, clone graph)
• Dynamic programming (climbing stairs, longest increasing subsequence)
• Advanced problems (regular expression matching, median of two sorted arrays)

Senior engineers (L5+) field system design sessions covering global-scale services like Google Maps, YouTube streaming, Google Docs collaboration, or distributed web crawlers. Interviewers expect explicit trade-offs around latency, availability, and storage.

Geo Hiring Signals (Google)

• US & Canada: Systems design depth and security/privacy considerations are scrutinized heavily in Bay Area and Seattle loops.
• Europe: Expect emphasis on GDPR awareness and localization challenges (especially in Zurich and Dublin).
• India & APAC: Coding rounds often skew harder; recruiters want evidence of working across time zones and with distributed teams.

Recommended Auto Interview AI Resources

• AI resume builder to align achievements with impact metrics before recruiter screens.
• ATS score checker to ensure keywords reflect Google’s role expectations.
• Mock interview simulator for spoken practice on STAR stories and technical explanations.

Case & Scenario Questions

Product and leadership roles combine product sense, estimation, and scenario design. Sample prompts:

• Improve YouTube’s recommendation engine.
• Design a messaging app for senior users.
• Estimate daily searches handled by Google.
• Improve a physical product (e.g., a water bottle) by reframing it as a user problem.

Interview Format

1. Resume review and recruiter screen (motivation, role fit).
2. Phone/virtual coding rounds on Google Docs-style editors.
3. Onsite or virtual loop (4–6 rounds): multiple coding rounds, one behavioral panel, system design for senior candidates, and occasionally a lunch interview.
4. Hiring committee review for unbiased decisions.
5. Team matching before offer finalization.

Difficulty & Candidate Experience

Average difficulty sits around 4.2/5. Candidates report respectful interviewers, but note the bar continues to rise with more emphasis on optimal solutions and clear articulation of trade-offs.

Preparation Playbook

• Target 200–300 LeetCode questions, prioritizing Google-tagged problems and medium difficulty.
• Master core patterns (sliding window, DFS/BFS, binary search, DP).
• Develop 5–7 STAR stories covering leadership, conflict resolution, and learning moments.
• For system design, review CAP theorem, data partitioning, caching, and load balancing.
• Use mock interviews to practice explaining thought processes under a 45-minute constraint.

Microsoft: The Growth Mindset Culture

Behavioral Focus

Microsoft interviews for a “growth mindset,” emphasizing learning, resilience, and collaboration. Expect prompts such as:

• Describe a mistake you made and what you learned.
• Why Microsoft? How would you improve a product you admire?
• Share a time you balanced trade-offs amid ambiguity.
• Outline how you prioritize competing deadlines.
• Discuss a moment of leadership or mentoring.

Quick Answer: What Does Microsoft Value in Interviews?

Microsoft favors candidates who document learnings, seek feedback proactively, and connect their work to customer impact. You should be prepared with at least one story that shows you changed course based on data and another where you coached a teammate.

Technical Expectations

Coding interviews center on practical data-structure problems:

• Arrays and strings (merge intervals, longest substring without repeats, pattern matching)
• Linked lists (add two numbers, copy with random pointer)
• Trees and graphs (validate BST, connected components)
• Dynamic programming (stock trading, climbing stairs variants)

Mid-senior roles add system design: URL shorteners, collaboration tools, file storage, real-time feeds, and ride-sharing logistics. Expect discussions around Azure services, API design, and security.

Geo Hiring Signals (Microsoft)

• US (Redmond) & Canada: Cloud fluency—Azure services, DevOps pipelines, and telemetry—shows up in nearly every loop.
• Europe: Accessibility and localization scenarios are common; highlight work with multilingual or regulated products.
• India: Expect combination rounds mixing DSA, low-level systems, and product sense; coding questions sometimes combine recursion with iterative refinements.

Recommended Auto Interview AI Resources

• Cover letter generator to align your “Why Microsoft” message with growth mindset language.
• AI-powered mock interview coach for spoken-answer drills on behavioral questions.
• AI job finder to identify Microsoft roles and tailor preparation to specific orgs.

Case & Scenario Questions

Product, PM, and managerial tracks explore feature prioritization, accessibility enhancements, and AI integration strategies—especially across Copilot, Teams, and Azure.

Interview Format

1. Recruiter connect (phone or LinkedIn outreach).
2. Online assessment (Codility/HackerRank) with 2–3 DSA problems.
3. Phone screen covering one or two coding tasks plus behavioral probes.
4. Onsite/virtual loop (4–5 rounds): coding, system design, behavioral integration; students may see campus-style whiteboarding.
5. As-Appropriate (AA) round with a senior leader if you are a strong hire.

Difficulty & Candidate Experience

Difficulty averages 3.8/5. Interviewers highlight collaboration, clarity, and the ability to iterate quickly. Candidates increasingly discuss Copilot and AI-assisted workflows.

Preparation Playbook

• Solve 150–200 LeetCode problems with Microsoft tags, biasing toward arrays/strings/linked lists.
• Practice in collaborative editors without autocomplete.
• Prepare STAR stories that demonstrate learning from setbacks.
• Refresh system design fundamentals with an Azure lens for SDE II+ roles.
• Stay current on Microsoft’s product roadmap (Azure AI, Copilot, Teams innovations).

Goldman Sachs: Precision Under Pressure

Behavioral Focus

Goldman Sachs assesses alignment with its core values: client service, integrity, excellence, and teamwork. Common prompts:

• Walk me through your résumé.
• Why Goldman Sachs? How does the firm make money?
• Share a time you stayed resilient amid setbacks.
• Describe an ethical dilemma and your response.
• Discuss recent financial news or M&A that caught your eye.
• Explain how you stay informed about markets.

Quick Answer: What Does Goldman Sachs Screen For?

Goldman Sachs screens for market fluency, ethical judgment under stress, and structured communication. Expect rapid follow-up questions that test whether your stories connect directly to client outcomes and measurable results.

Technical Expectations

The process combines quantitative reasoning, coding, and finance fundamentals:

• Online assessments tackling numerical computations, logical reasoning, and verbal analysis.
• Coding challenges on CoderPad/HackerRank: linked lists, sorting algorithms, hash maps, object-oriented design, API basics.
• Finance questions: DCF walkthroughs, valuation frameworks, revenue vs. cost synergies, Sharpe ratio limitations, portfolio metrics.
• Brain teasers and mental math under time pressure.

Geo Hiring Signals (Goldman Sachs)

• New York & London: Expect in-depth discussions on regulatory shifts, cross-border deals, and client confidentiality.
• India (Bengaluru, Hyderabad): Technical screens often include API design and Java/Python fundamentals alongside finance cases.
• APAC hubs: Market questions tilt toward regional FX trends and sovereign risk scenarios.

Recommended Auto Interview AI Resources

• Resume job matcher to find roles aligned with investment banking, markets, or engineering tracks.
• ATS score checker to thread keywords like “DCF,” “LBO,” and “market risk” into your CV.
• AI cover letter generator for compliant, client-focused motivation statements.

Case & Scenario Questions

Expect investment scenarios (e.g., allocating a fixed budget), market explanations, and ethical hypotheticals about client interactions.

Interview Format

1. Application plus resume-based screening.
2. Online Assessment 1: 66-question aptitude test with negative marking.
3. Online Assessment 2: coding, quantitative aptitude, core CS MCQs, and written behavioral responses.
4. HireVue video interview with AI feedback.
5. Technical rounds (2–3 sessions) covering DSA, puzzles, and tech stack familiarity.
6. Superday/panel with back-to-back interviews, valuation drills, market discussions.
7. Final HR/managerial round.

Difficulty & Candidate Experience

Difficulty hovers around 4.5/5 due to multiple elimination rounds and high-stakes panels. Feedback is mixed: the process is rigorous but yields fast momentum if you perform well.

Preparation Playbook

• Drill numerical reasoning, probability, ratios, and mental math daily.
• Solve 150–200 medium DSA problems; emphasize clean, well-tested code.
• Master valuation (DCF, comparables, precedent transactions) and deal structuring.
• Track macroeconomic shifts, deal activity, and Goldman’s latest initiatives.
• Practice HireVue responses with AI interview simulators to optimize delivery.

Morgan Stanley: Strategic Thinking Meets Analytical Rigor

Behavioral Focus

Morgan Stanley probes for integrity, teamwork, and client-first thinking. Be ready to discuss:

• Career goals and long-term aspirations.
• A time you handled conflict within a team.
• Moments where you detected and solved a looming issue.
• Recent market trends or transactions that interest you.
• Ethical dilemmas and how you upheld firm values.

Quick Answer: What Does Morgan Stanley Prioritize?

Morgan Stanley prioritizes structured problem solvers who can pivot between technology and finance conversations, relationship builders who can advise clients, and professionals who show ownership of deliverables from kickoff to post-mortem.

Technical Expectations

Requirements vary by role:

• Technology tracks: deep JavaScript knowledge (polyfills, closures, event loop), React or Angular component design, API integration, performance tuning, moderate DSA.
• Finance tracks: valuation models, financial statements, sector analyses, Excel modeling, risk metrics.
• Cross-functional: SQL, database design, API architecture, cloud fundamentals.

Geo Hiring Signals (Morgan Stanley)

• US (NYC) & UK: Expect cross-border deal discussions and questions about compliance with SEC/FCA frameworks.
• India (Mumbai, Bengaluru): Technical rounds dive into front-end performance, API resiliency, and hybrid cloud setups.
• Hong Kong & Singapore: Interviewers focus on macro trends across APAC wealth management and capital markets.

Recommended Auto Interview AI Resources

• Portfolio-ready resume builder to highlight technology and finance achievements in tandem.
• Interview Q&A simulator for run-throughs of ethical and advisory scenarios.
• Career analytics dashboard to ensure keyword coverage for both tech stacks and financial modeling.

Case & Scenario Questions

Candidate case studies may cover IPO valuation for a hypothetical startup, advising clients through market swings, or diagnosing underperforming portfolios.

Interview Format

1. Application submission.
2. HireVue video screening (3–8 questions, 30–90 seconds per response).
3. HackerRank or coding assessment for tech roles (JavaScript + framework challenges under proctoring).
4. Technical rounds (often two to three) covering coding, architecture, and current projects.
5. Professional fitment interviews that assess attitude, mentorship fit, and communication.
6. Additional panels with global team members for cross-border roles.
7. HR and compensation discussions.

Difficulty & Candidate Experience

Difficulty scores around 3.9/5. Candidates cite lengthy processes and deep dives into both technical detail and business context, especially for hybrid tech-finance roles.

Preparation Playbook

• Refine JavaScript fundamentals beyond syntax; build complex components from scratch.
• Review valuation frameworks and market drivers if targeting finance divisions.
• Prepare STAR stories around leadership, analytics, and client service.
• Read Morgan Stanley research notes and press releases for sector insight.
• Simulate HireVue responses and remote whiteboarding sessions.

JP Morgan: Scale, Speed, and Substance

Behavioral Focus

JP Morgan values resilience, teamwork, and ownership. Core prompts include:

• Walk through your background and current projects.
• Why JP Morgan and why this role?
• Describe a time you simplified a complex concept for a stakeholder.
• Explain how you helped a struggling teammate.
• Discuss moments when you balanced competing priorities under pressure.

Quick Answer: What Does JP Morgan Expect from Candidates?

JP Morgan expects clear communicators who ship production-ready code, teammates who support others during incidents, and problem solvers who can quantify risk, cost, or customer impact in real time.

Technical Expectations

Coding interviews emphasize practical implementation and clarity:

• Frequency maps, anagram detection, prefix sums, sliding window, and greedy techniques.
• Arrays, strings, hash maps, linked lists, and tree traversal fundamentals.
• Clean coding practices with helper functions and guard clauses.
• Technology stacks such as Kubernetes, Terraform, CI/CD pipelines, and database schema design for DevOps or SRE roles.
• SQL, real-time data flows, and domain-specific knowledge for trading or risk teams.

Geo Hiring Signals (JP Morgan)

• US (Jersey City, Columbus) & UK (Bournemouth): DevOps maturity and secure-by-design practices are key; be ready to discuss SOC or ISO frameworks.
• India (Mumbai, Hyderabad, Bengaluru): Pair programming rounds often combine DSA with debugging existing code.
• Singapore & Hong Kong: Expect questions around regional regulatory tech, payments, and latency-sensitive systems.

Recommended Auto Interview AI Resources

• Incident response storytelling worksheet to frame operational excellence wins.
• DevOps-focused mock interview drills for scenario-based rehearsals.
• Resume keyword enhancer to map skills like Kubernetes, Terraform, and risk analytics to recruiter searches.

Case & Scenario Questions

You may be asked to design deployment architectures, troubleshoot production outages, or optimize database queries. Scenario prompts gauge both technical depth and communication.

Interview Format

1. Application (often via referrals or campus events).
2. HackerRank assessment with 2–3 medium DSA problems.
3. HireVue video interview focusing on teamwork and communication.
4. Technical rounds (two to three) with live coding and technology deep dives.
5. Managerial round exploring leadership, conflict management, and long-term goals.
6. Final panel or onsite for certain roles and regions.

Difficulty & Candidate Experience

Difficulty averages 3.7/5. Interviewers prioritize clarity, correctness, and resilience. Expect thorough background verification after an offer.

Preparation Playbook

• Practice DSA essentials with time-boxed HackerRank or CoderPad sessions.
• Emphasize clean code, unit-style testing, and explicit complexity analysis.
• Build STAR stories highlighting collaboration, mentorship, and problem ownership.
• For platform roles, study microservices, logging pipelines, and cloud infrastructure.
• Stay informed about JP Morgan’s technology investments and product launches.

Comparison at a Glance

Geo-Aware Preparation Tips

• United States & Canada: Expect longer processes with multiple loops. Emphasize diversity contributions and community impact.
• United Kingdom & Europe: Prepare for competency-based behavioral frameworks and detailed discussions about regulatory environments.
• India: Online assessments are rigorous filters; invest time in proctored coding practice and campus-specific drives.
• Asia-Pacific: Showcase cross-cultural collaboration, regional market knowledge, and flexibility with time zones.
• Hybrid/Remote Roles: Demonstrate asynchronous communication skills, documentation habits, and experience collaborating across geographies.

Key Action Checklist

1. Map your dream roles using the AI job finder and note the location-specific signals listed above.
2. Refresh your resume and LinkedIn with measurable impact statements via the AI resume builder and ATS checker.
3. Plan 7 STAR stories that cover leadership, conflict resolution, learning from failures, and client impact.
4. Schedule alternating practice blocks: one day of timed DSA/system design drills, one day of behavioral and market/strategy rehearsals.
5. Record mock answers with the mock interview simulator and tighten responses to 90 seconds for voice-search and HireVue compatibility.

Conclusion: Patterns Across Elite Firms

Despite sector differences, elite firms share three converging trends:

1. AI-infused assessments now evaluate tone, pacing, and collaborative behaviors alongside code accuracy. Candidates must validate AI suggestions and show judgment in real-world coding environments.
2. Higher hiring bars demand deeper preparation—more problems solved, broader system design knowledge, and sharper behavioral storytelling.
3. Scenario-based evaluations simulate day-to-day work, from debugging legacy services to advising clients through market turbulence.

Successful candidates blend technical precision with business clarity, communicate trade-offs confidently, and adapt gracefully to ambiguous challenges. Preparation that balances hard skills, soft skills, and company-specific research remains the decisive differentiator.

FAQ

How many coding problems should I solve before interviewing with these firms?
Most successful candidates complete 150–300 well-chosen problems, focusing on reusable patterns rather than memorizing specific solutions.

Do HireVue or AI video interviews matter as much as live rounds?
Yes. Many firms eliminate candidates at this stage, so rehearse concise, energetic answers and maintain professional body language.

How do I stand out if everyone uses AI tools?
Use AI to accelerate brainstorming, but always verbalize how you validate suggestions, handle edge cases, and ensure production-readiness.

What if I get downleveled during team matching?
Clarify expectations early, emphasize scope ownership in your stories, and highlight cross-functional impact to reinforce seniority.

How often should I refresh my preparation once interviews are done?
Schedule monthly review sessions to stay sharp on core patterns, new product announcements, and macroeconomic developments.

What is the fastest way to get interview-ready in two weeks?
Front-load company research and behavioral prep (days 1–3), run daily 60-minute coding sprints (days 4–10), and close with back-to-back mock loops that combine technical and STAR answers (days 11–14).

How do interview expectations change by geography?
North America emphasizes innovation and ownership, Europe stresses compliance and localization, India prioritizes high signal-to-noise DSA and blended rounds, and APAC leans on cross-border collaboration plus real-time market awareness.

Sources

• Google Careers – How We Hire
• Microsoft Interview Tips
• Goldman Sachs Interview Resources
• Morgan Stanley Interview Preparation
• JP Morgan Interview Experiences – GeeksforGeeks
• Pragmatic Engineer – The Reality of Tech Interviews
• HackerRank – AI-Assisted Technical Assessments