Pretty standard easy-level stuff, nothing that should trip anyone up.
Start by clarifying the problem constraints and edge cases, then outline a brute-force solution before optimizing. For each problem, choose the appropriate data structure and algorithm, and test with examples to ensure correctness. Manage your time by allocating roughly equal time to both problems and leaving buffer for review.
Pro tip: In timed assessments, prioritize passing all test cases for one problem before moving to the next; partial credit is often awarded per problem, so securing one complete solution is better than two incomplete ones.
Read both problems carefully, note input/output formats, constraints, and edge cases. Ask clarifying questions if allowed, and identify the core operation for each.
For each problem, decide on an algorithm (e.g., two-pointer, hash map, sorting) based on constraints. Estimate time and space complexity to ensure it fits within limits.
Write clean, modular code for one problem at a time. Test with provided examples and additional edge cases (empty arrays, duplicates, large inputs) to catch bugs early.
If time permits, optimize the solution further (e.g., reduce space, improve time). Review code for off-by-one errors and ensure both problems are solved.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
This was more involved than I expected for an intern round.
Start by clarifying requirements and constraints, then design a clean OOP model with clear responsibilities and interfaces. Implement core functionality with unit tests, and demonstrate extensibility by adding new account types via inheritance or composition. Discuss trade-offs and design patterns used.
Pro tip: Emphasize testability and separation of concerns from the start; show how your design makes adding new account types trivial without modifying existing code (Open/Closed Principle).
Ask questions to understand scope: What operations are needed? What account types? What are the constraints (e.g., concurrency, persistence)? This shows you think before coding.
Identify core entities (Account, Transaction, Customer) and their relationships. Define interfaces and abstract classes to allow extensibility. Consider patterns like Strategy for account behaviors.
Write code for the base system, focusing on single responsibility and dependency injection. Write unit tests for each component, covering edge cases and mocking dependencies.
Add new account types (e.g., Savings, Checking) by extending the base Account class or using composition. Show how existing tests still pass and add new tests for new types.
Explain design decisions: why inheritance vs composition, how you ensured testability, and potential improvements (e.g., using a factory for account creation).
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Craft a concise narrative that connects your programming origin story to your growth as an engineer, highlighting adaptability through varied projects and experiences. Focus on how each phase (learning, building, collaborating) shaped your problem-solving and ability to thrive in ambiguous situations, which aligns with Shopify's fast-paced environment.
Pro tip: Tie your hobbies and side projects to transferable skills like debugging, iteration, or user empathy—showing that you're always learning and applying engineering thinking beyond work. Avoid listing technologies; instead, emphasize the impact and lessons from each experience.
Briefly explain how you got into programming, focusing on the initial spark and early challenges that taught you resilience and curiosity.
Highlight 1-2 key projects (professional or personal) that demonstrate your technical skills and ability to navigate ambiguity, such as unclear requirements or shifting priorities.
Mention hobbies or side projects that reflect your passion for building, learning, or collaborating—showing how they contribute to your engineering mindset.
Describe a specific experience (e.g., a failure, mentorship, or cross-functional collaboration) that shaped your approach to problem-solving and teamwork.
Summarize how your background prepares you to thrive in Shopify's dynamic environment, emphasizing adaptability and a bias for action.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Select 1-2 specific principles or CEO email ideas that genuinely resonated with you, then connect them to concrete examples from your past work that demonstrate adaptability and comfort with ambiguity. Show how these ideas align with your natural working style rather than just praising the documents.
Pro tip: Reference a specific principle by name and explain how you've already applied it in a real scenario—this proves you internalized the material rather than just skimmed it. Avoid generic praise like 'I loved the focus on merchants'; instead, tie it to a tangible engineering decision you made.
Pick one or two specific ideas from the principles document or CEO emails that genuinely stood out to you. Be precise—name the principle and briefly explain why it resonated.
Describe a concrete example from your past work where you embodied that principle. Focus on a situation involving ambiguity, shifting priorities, or self-directed problem-solving.
Explain how you navigated uncertainty in that example—what you did when requirements were unclear, how you made decisions, and how you adjusted as things changed.
Tie your example back to how you'd operate at Shopify, showing how your working style aligns with the company's values and the demands of the role.
Wrap up in under two minutes, ensuring your answer feels genuine and not rehearsed. Avoid over-explaining; let the connection speak for itself.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.