Amazon Leadership Principles Questions
Demonstrate familiarity with Amazon leadership principles and how they apply to program and project decisions. Explain principles such as customer obsession, deliver results, think big, and dive deep, and practice mapping your behaviors and examples to those principles when describing trade offs, prioritization, and stakeholder influence.
EasyTechnical
72 practiced
How do you foster a 'Learn and Be Curious' culture on your engineering team? Provide specific initiatives (e.g., engineering book club, hack days, shadowing), meeting cadences, and KPIs you would track to evaluate program effectiveness over a quarter.
EasyTechnical
70 practiced
Your product has accrued many small services and custom integrations over time, increasing complexity. As an Engineering Manager, describe how you would apply 'Invent and Simplify' to reduce complexity without disrupting current delivery. Provide a 3-step plan with short timeboxes and explain how you'd measure success.
HardTechnical
77 practiced
You manage a mature product with high technical debt and constant feature demands. Propose a multi-quarter plan balancing debt reduction and new features that aligns with 'Deliver Results', 'Frugality', and 'Think Big'. Outline prioritization approach, funding model (e.g., percent-of-sprint, dedicated squads), milestones, and KPIs to track technical debt reduction and feature velocity.
HardTechnical
68 practiced
You're asked to launch a personalization feature that would improve engagement but requires sharing additional customer data across services. Legal and privacy raise concerns. As an Engineering Manager, walk through an ethical decision-making framework you would use: which leadership principles you prioritize, who you involve, what technical mitigations you require, and the acceptance criteria for proceeding.
HardTechnical
52 practiced
Your production service is experiencing intermittent latency spikes and occasional failures. As the Engineering Manager, describe how you would lead a 'Dive Deep' investigation: what telemetry/logs/traces you require, how you would structure hypotheses and timeboxed experiments, how you would organize the team (roles and rotations), and what post-incident changes you'd mandate.
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