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Google·Software Engineer·Onsite - Multi Round·Junior

JuniorPending
May 2026Europe

Summary

Went through the full Google SRE-SWE loop in Europe: a technical phone screen, two onsite coding rounds, and a behavioral. Phone screen and behavioral felt solid, one coding round went fine, but the other had some real stumbles that I'm still not sure I recovered from well enough.

Questions Asked (10)

Q1

Given a grid, count the number of valid paths from one corner to another, then handle additional constraints on which paths are valid, and finally optimize for space.

Algorithms & Data Structures
Author's notes

Got the base problem without much trouble and reasoned through complexity fine.

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AI HintsAI Generated

Suggested Approach

Start with the classic dynamic programming solution for counting paths on a grid without obstacles, then extend it to handle obstacles by treating blocked cells as having zero paths. Finally, optimize space by using a 1D DP array and updating it in place, explaining the recurrence and complexity trade-offs.

Pro tip: Explicitly discuss how you would handle large grids that don't fit in memory, such as using combinatorial formulas or streaming approaches, to show depth beyond the basic DP.

1. Clarify the problem

Ask about grid size, movement directions (e.g., only right and down), start and end points, and any constraints like obstacles or time/space limits.

2. Base DP solution

Define dp[i][j] as the number of paths to cell (i,j). Initialize first row and column to 1, then use dp[i][j] = dp[i-1][j] + dp[i][j-1].

3. Handle obstacles

If a cell is blocked, set dp[i][j] = 0. Adjust initialization for first row/column: once an obstacle is encountered, all subsequent cells in that row/column have 0 paths.

4. Space optimization

Use a 1D array dp of size n (columns). For each row, update dp[j] = dp[j] + dp[j-1], with dp[0] initialized to 1 if no obstacle in first column.

5. Analyze complexity

Time complexity is O(m*n) and space complexity is O(n) after optimization. Discuss potential further optimizations like using combinatorial formulas if no obstacles.

Key Points to Mention

  • Dynamic programming recurrence: dp[i][j] = dp[i-1][j] + dp[i][j-1]
  • Handling obstacles by setting dp[i][j] = 0 and adjusting first row/column
  • Space optimization using a 1D array and in-place updates
  • Time and space complexity analysis (O(m*n) time, O(n) space)
  • Edge cases: empty grid, start or end blocked, no obstacles
  • Alternative approaches: combinatorial formula (if no obstacles) or BFS/DFS for small grids

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q2

Find the longest valid path in a grid using DFS/backtracking, with specific movement constraints between adjacent cells.

Algorithms & Data Structures
Author's notes

This is the one I keep replaying.

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AI HintsAI Generated

Suggested Approach

Clarify the movement constraints and what constitutes a valid path, then model the grid as a graph and use DFS with backtracking to explore all paths, tracking the longest. Optimize with memoization or pruning if revisiting cells is allowed, and analyze time/space complexity.

Pro tip: Discuss how to handle cycles and avoid infinite loops by marking visited cells, and mention that if the grid is large, you might need to consider iterative deepening or dynamic programming for efficiency.

1. Clarify the problem

Ask questions to understand the movement constraints, definition of a valid path (e.g., can cells be revisited?), and what 'longest' means (number of cells or edges).

2. Model as a graph

Treat each cell as a node and valid moves as directed edges. This abstraction helps in applying standard graph traversal techniques.

3. Design DFS with backtracking

Implement a recursive DFS that explores all valid moves from the current cell, marks cells as visited to avoid cycles, and backtracks to explore other paths.

4. Optimize and handle edge cases

Consider memoization if revisiting is allowed, prune paths that cannot beat the current longest, and handle edge cases like empty grid or no valid moves.

5. Analyze complexity and test

Discuss time and space complexity (e.g., O(4^(m*n)) worst-case for DFS) and propose test cases to validate the solution.

Key Points to Mention

  • Movement constraints: specify allowed directions (up, down, left, right, diagonals?) and any conditions (e.g., increasing values).
  • Visited tracking: use a boolean array or modify grid in-place to avoid revisiting cells, ensuring no infinite loops.
  • Backtracking: unmark cells after exploring to allow other paths to use them.
  • Pruning: if the maximum possible remaining path length plus current length is less than the best found, stop exploring.
  • Memoization: if revisiting is allowed, use DP to store longest path from each cell, but careful with cycles.
  • Complexity: worst-case exponential time, but with constraints may be polynomial; space O(m*n) for recursion stack and visited.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q3

Solve a problem involving a heap or priority queue, analyze time and space complexity.

Algorithms & Data Structures
Author's notes

Spotted the pattern fast and just implemented it.

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AI HintsAI Generated

Suggested Approach

First, clarify the problem and identify why a heap is appropriate (e.g., need efficient access to min/max). Then, outline the algorithm, implement it with clear code, and analyze time and space complexity, discussing trade-offs and potential optimizations.

Pro tip: Always discuss the trade-offs between using a heap and other data structures like balanced BSTs or sorting, and mention real-world scenarios where heap operations are critical.

1. Understand the Problem

Ask clarifying questions to ensure you understand the input, output, constraints, and edge cases. Confirm that a heap is the right tool for the job.

2. Design the Algorithm

Outline the steps of your approach, specifying how you will use heap operations (push, pop, peek) and any auxiliary data structures.

3. Implement the Solution

Write clean, modular code, using a heap library or implementing one if required. Handle edge cases and ensure correctness.

4. Analyze Complexity

Derive the time complexity by summing the costs of heap operations and other steps. Determine space complexity, including the heap and any extra storage.

5. Optimize and Discuss Trade-offs

Consider if the solution can be improved (e.g., using a different data structure or algorithm) and discuss the trade-offs in terms of time, space, and simplicity.

Key Points to Mention

  • Heap property and operations (insert, extract-min/max, heapify) and their time complexities.
  • Time complexity analysis: O(n log n) for building a heap from n elements, O(log n) for insert/delete, O(1) for peek.
  • Space complexity: O(n) for storing the heap, plus any additional data structures.
  • Comparison with alternative approaches (e.g., sorting, balanced BSTs) and when a heap is preferable.
  • Edge cases: empty heap, duplicate elements, large input sizes.
  • Real-world applications: priority queues, Dijkstra's algorithm, median maintenance, task scheduling.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q4

Tell me about a time you had to manage competing priorities or a heavy workload.

Adaptability & Ambiguity
Author's notes

Pulled from real infrastructure project work.

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AI HintsAI Generated

Suggested Approach

Use the STAR method to describe a specific situation where you had to prioritize multiple tasks or projects. Focus on how you assessed impact and urgency, communicated with stakeholders, and made trade-offs to deliver results. Highlight the outcome and what you learned about managing competing priorities.

Pro tip: Emphasize how you used data or metrics to prioritize tasks, and how you proactively communicated with stakeholders to manage expectations. This shows you're not just reactive but strategic in handling workload.

1. Set the Context

Briefly describe the situation: what projects or tasks were competing, and why they were important. Mention any constraints like deadlines or limited resources.

2. Explain Your Prioritization Process

Detail how you evaluated tasks based on impact, urgency, and effort. Mention any frameworks or tools you used (e.g., Eisenhower Matrix, RICE scoring) and how you involved stakeholders.

3. Describe Your Actions

Explain what you did to manage the workload: delegating, negotiating deadlines, breaking down tasks, or focusing on high-impact work. Highlight communication with your team or manager.

4. Share the Outcome

Quantify the results if possible: met deadlines, delivered key features, improved efficiency, or received positive feedback. Mention any trade-offs and how they were handled.

5. Reflect on Learnings

Summarize what you learned about prioritization and time management, and how you've applied these lessons in subsequent roles or projects.

Key Points to Mention

  • Specific prioritization framework or criteria used (e.g., impact vs. urgency)
  • Communication with stakeholders to align on priorities and expectations
  • Trade-offs made and how you handled them (e.g., delaying low-priority tasks)
  • Quantifiable results (e.g., delivered X feature on time, reduced backlog by Y%)
  • Ability to stay calm under pressure and adapt to changing priorities
  • Lessons learned and how you improved your process for future workload management

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q5

Describe a situation where you helped someone get up to speed or integrate into a team.

Cross-functional Alignment
Author's notes

Had a decent onboarding story from a cloud project.

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AI HintsAI Generated

Suggested Approach

Use the STAR method to describe a specific instance where you onboarded a teammate, focusing on the actions you took to accelerate their learning and integration. Highlight the measurable outcomes for the individual and the team, and connect it to Google's collaborative culture.

Pro tip: Emphasize how you tailored your approach to the person's learning style and proactively removed blockers, showing empathy and leadership beyond just technical guidance.

1. Set the Context

Briefly describe the situation: who you helped, their background, and why they needed onboarding (e.g., new hire, transfer, or struggling with a project).

2. Identify the Challenge

Explain the specific obstacles they faced, such as unfamiliar codebase, missing documentation, or team dynamics, to show you understood their needs.

3. Describe Your Actions

Detail the concrete steps you took: creating a learning plan, pair programming, code reviews, introducing them to key stakeholders, and providing regular feedback.

4. Highlight the Outcome

Share the results: how quickly they became productive, their contributions, and any positive impact on team morale or project delivery.

5. Reflect and Connect

Summarize what you learned and how it demonstrates your ability to foster collaboration and inclusion, aligning with Google's values.

Key Points to Mention

  • Specific actions taken to onboard the person (e.g., documentation, pair programming, mentorship)
  • Tailoring the approach to the individual's learning style and background
  • Proactive communication and regular check-ins to track progress
  • Measurable outcomes (e.g., time to first commit, increased team velocity)
  • Impact on team dynamics and collaboration
  • Connection to Google's culture of mentorship and cross-functional alignment

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q6

Tell me about a time you delivered under a tight deadline with significant ambiguity.

Adaptability & Ambiguity
Author's notes

Went with a project delivery story where requirements kept shifting.

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AI HintsAI Generated

Suggested Approach

Use the STAR method to structure your answer, focusing on a specific project where you had to make decisions with incomplete information under time pressure. Highlight how you prioritized tasks, communicated risks, and delivered a working solution. Emphasize the trade-offs you made and the impact of your delivery.

Pro tip: Show that you proactively sought clarification and validated assumptions early, rather than waiting for perfect information. Google values engineers who can navigate ambiguity by breaking down problems and iterating quickly.

1. Set the Context

Briefly describe the project, the tight deadline, and the sources of ambiguity (e.g., unclear requirements, missing documentation, evolving scope).

2. Identify the Core Challenge

Explain what made the deadline tight and the ambiguity significant, and why it mattered to the business or users.

3. Describe Your Actions

Detail the steps you took to mitigate ambiguity: asking targeted questions, making assumptions, prioritizing features, and communicating with stakeholders.

4. Highlight the Outcome

Share the results: what you delivered, how it performed, and any metrics or feedback that show success despite the constraints.

5. Reflect and Learn

Summarize what you learned and how you would apply those lessons to future ambiguous, high-pressure situations.

Key Points to Mention

  • Prioritization: how you focused on the most critical features first
  • Communication: keeping stakeholders informed and managing expectations
  • Decision-making under uncertainty: making reasonable assumptions and validating them
  • Technical trade-offs: choosing pragmatic solutions over perfect ones
  • Collaboration: working effectively with cross-functional teams
  • Measurable impact: delivering on time and achieving key results

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q7

Describe a time you challenged a risky assumption on a project.

Technical Trade-offsStakeholder Management
Author's notes

Used an architecture tradeoff situation where I pushed back on a design decision that had downstream reliability implications.

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AI HintsAI Generated

Suggested Approach

Use the STAR method to structure your answer, focusing on a specific project where you identified and challenged a risky assumption. Highlight how you gathered data, communicated your concerns, and influenced the team to reassess, leading to a better outcome. Emphasize the technical trade-offs and stakeholder management aspects.

Pro tip: Show that you not only challenged the assumption but also proposed a viable alternative and quantified the risks and benefits. This demonstrates proactive problem-solving and business acumen, which is highly valued at Google.

1. Set the Context

Briefly describe the project, your role, and the risky assumption that was being made. Ensure the assumption is clearly technical or related to trade-offs.

2. Identify the Risk

Explain how you recognized the assumption as risky, including any data, metrics, or expert opinions that supported your concern.

3. Challenge and Communicate

Describe how you raised the issue with stakeholders, the approach you took to communicate the risk, and how you handled pushback or resistance.

4. Propose and Validate

Detail the alternative solution or validation experiment you proposed, and how you worked with the team to test or implement it.

5. Outcome and Learning

Share the results: what was the impact on the project, and what did you learn about challenging assumptions or managing stakeholders?

Key Points to Mention

  • Specific technical details of the assumption and why it was risky (e.g., scalability, performance, security).
  • Data or evidence you used to challenge the assumption (e.g., benchmarks, user research, expert consultation).
  • How you navigated stakeholder dynamics, including convincing senior engineers or product managers.
  • The trade-offs considered and how you balanced technical debt, timelines, and business goals.
  • The outcome: how the project benefited from your intervention (e.g., avoided outage, improved performance).
  • Reflection on what you learned and how you apply this lesson to future projects.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q8

How do you adapt how you communicate technical information depending on your audience?

Stakeholder ManagementCross-functional Alignment
Author's notes

Talked through a specific case of presenting infrastructure decisions to non-technical stakeholders.

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AI HintsAI Generated

Suggested Approach

Emphasize that you first assess the audience's technical background and goals, then tailor your communication style, depth, and terminology accordingly. Use concrete examples from your experience to illustrate how you've successfully adapted to different audiences, such as engineers, product managers, and executives.

Pro tip: Show that you not only adapt your message but also actively confirm understanding and adjust in real-time based on feedback. This demonstrates strong communication skills and empathy, which are highly valued at Google.

1. Identify Audience and Purpose

Determine who you're speaking to, their technical expertise, and what they need from the communication. Clarify the goal: are you informing, persuading, or seeking input?

2. Tailor Content and Language

Adjust the level of technical detail, jargon, and examples to match the audience. For non-technical stakeholders, focus on impact and analogies; for engineers, dive into specifics.

3. Choose the Right Medium and Structure

Select the appropriate format (e.g., code comments, diagrams, presentations) and organize the information logically for the audience. Use visuals for complex concepts when helpful.

4. Confirm Understanding and Adapt

Check for comprehension through questions or feedback, and be ready to rephrase or provide more context. Adjust your approach in real-time based on reactions.

5. Reflect and Improve

After the interaction, reflect on what worked and what didn't. Seek feedback to continuously improve your communication adaptability.

Key Points to Mention

  • Assessing the audience's technical background and needs before communicating
  • Using analogies and avoiding jargon for non-technical stakeholders
  • Providing detailed technical explanations for engineering peers
  • Focusing on business impact and outcomes for executives
  • Using visual aids like diagrams to simplify complex ideas
  • Actively seeking feedback to ensure understanding and adjust accordingly

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q9

Tell me about a time you gave someone difficult feedback.

Conflict Resolution
Author's notes

Short answer, kept it simple.

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AI HintsAI Generated

Suggested Approach

Choose a specific instance where you delivered constructive feedback to a peer or teammate, focusing on the situation, your approach, and the positive outcome. Emphasize empathy, data-driven observations, and how you maintained the relationship while improving performance.

Pro tip: Show that you tailored the feedback to the individual's personality and work style, and that you followed up to ensure improvement—this demonstrates emotional intelligence and leadership.

1. Set the Context

Briefly describe the situation, the person involved, and why feedback was necessary. Keep it concise and avoid sensitive details.

2. Explain Your Approach

Detail how you prepared and delivered the feedback, focusing on specific behaviors and using 'I' statements to avoid sounding accusatory.

3. Describe the Reaction and Resolution

Share how the person responded and what actions were taken to address the issue, highlighting collaboration and support.

4. Highlight the Outcome

Conclude with the positive results, such as improved performance, stronger teamwork, or personal growth for both parties.

5. Reflect and Learn

Briefly mention what you learned from the experience and how it has shaped your approach to giving feedback in the future.

Key Points to Mention

  • Specific, observable behavior rather than personal traits
  • Empathy and respect for the individual's perspective
  • Use of data or concrete examples to support feedback
  • Focus on improvement and future actions
  • Follow-up to ensure the feedback was effective
  • Positive impact on team dynamics or project outcomes

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q10

What do you look for in a manager?

Adaptability & Ambiguity
Author's notes

Honestly a bit of a curveball to end on.

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AI HintsAI Generated

Suggested Approach

Focus on the qualities that enable you to do your best work, such as clear communication, trust, and support for autonomy. Tie these to Google's engineering culture, emphasizing how a manager can help you navigate ambiguity and deliver impact. Keep your answer concise and authentic, avoiding generic clichés.

Pro tip: Mention that you also value a manager who can adapt their style to the team's needs and the project's phase, showing you understand that great management isn't one-size-fits-all. This demonstrates maturity and flexibility, key traits for Google engineers.

1. Clarify your core values

Start by stating the top 2-3 qualities you look for, such as trust, clear communication, and support for autonomy. These should align with your personal work style and the role.

2. Connect to impact and growth

Explain how these qualities help you be more effective, such as enabling you to take risks, learn from failures, and deliver high-quality work. Link to Google's focus on innovation and impact.

3. Show adaptability

Acknowledge that different situations require different management styles, and express appreciation for managers who can adjust their approach. This shows you understand the dynamic nature of engineering work.

4. Provide a brief example

If possible, give a quick example of a manager who exemplified these qualities and how it positively affected your work. This adds credibility and makes your answer memorable.

5. Tie back to the role

Conclude by relating your preferences to the Software Engineer role at Google, emphasizing how the right manager can help you navigate ambiguity and contribute to team success.

Key Points to Mention

  • Trust and psychological safety: feeling safe to take risks and speak up
  • Clear communication and expectations: knowing what success looks like
  • Autonomy and empowerment: freedom to solve problems your way
  • Support for growth and learning: feedback and mentorship
  • Adaptability: manager adjusts style based on team and project needs
  • Alignment with Google's culture: innovation, impact, and ambiguity

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.