Scalability and Code Organization Questions

Focuses on designing software and codebases that remain maintainable and performant as features and user load grow. Areas include modularity and separation of concerns, component and API boundaries, when and how to refactor, trade offs between monolith and service oriented architectures, data partitioning and caching strategies, performance optimization, testing strategies, dependency management, code review practices, and patterns for maintainability and evolvability. Interview questions may ask candidates to reason about design choices, identify coupling and cohesion issues, and propose practical steps to evolve an existing codebase safely.

EasyTechnical

30 practiced

As a BI lead you must convince engineering leadership to invest in a shared component library for dashboard widgets. Prepare a one-paragraph technical argument that summarizes ROI, risk reduction, onboarding benefits, and how you would measure success after 6 months.

MediumTechnical

32 practiced

Write a short Python decorator that memoizes the result of an expensive metric calculation function but invalidates cache entries after a time-to-live (TTL). The decorator should be thread-safe and suitable for use inside a WSGI app. Provide the decorator and a brief example usage.

MediumTechnical

57 practiced

Describe how you would structure a repository for a BI platform that includes: backend APIs, shared metric definitions, visualization components (React/Power BI templates), and deployment manifests. Explain folder layout, packaging strategy for shared modules, and how to enforce boundaries through CI.

MediumTechnical

33 practiced

Implement a small interface (pseudocode or Python) for registering metric computations with metadata: name, owner, input-signature, expected-cost, and TTL. Then write a sample registry lookup that returns the best computation strategy (direct compute vs cached precompute) based on expected_cost and current load. Keep code concise.

EasyTechnical

40 practiced

Propose a minimal set of documentation (README sections, diagrams, and examples) that should accompany any new BI service or metric definition to ensure future maintainability and safe evolution. Explain why each item matters.

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