The scenario wanted you to pick between a few options: loop in your lead with context and ask for guidance, set up a meeting with another teammate, keep grinding alone until the next team sync, revert the code, or just flag that the deadline is at risk.
Show that you prioritize customer impact and data-driven decision-making by quickly assessing the race condition's severity and reproducibility, then proposing a mitigation plan. Communicate transparently with your team lead, framing the issue as a risk with options rather than just a problem, and align on a path forward that balances deadline and quality.
Pro tip: Demonstrate Amazon's Leadership Principles by taking ownership (e.g., 'I would not ship a known critical bug') and insisting on high standards, while also showing bias for action by suggesting a short-term fix (like a feature flag) to meet the deadline if safe.
Quickly determine the race condition's potential impact (e.g., data corruption, customer-facing errors) and how often it occurs. Gather evidence such as logs, reproduction steps, and affected code paths.
Identify possible solutions: a quick fix (e.g., locking, retry logic), a temporary workaround (e.g., disabling the feature), or delaying the release. Estimate effort and risk for each.
Schedule a brief meeting or send a concise message summarizing the issue, impact, options, and your recommendation. Be clear about trade-offs and ask for input.
Collaborate with the team lead to choose the best path, considering deadline, customer impact, and technical debt. Document the decision and next steps.
Implement the chosen solution, monitor for issues, and keep the team informed. After the deadline, conduct a retrospective to prevent similar issues.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.