DoorDash DevOps / SRE Interview Questions

Behavioral Questions (15)

1. 1.Describe the last time you had to respond to a production incident that required immediate action. Walk me through your decision-making process under pressure.

   easy~3 min

   What interviewers look for

   • Took immediate action to mitigate customer impact rather than spending excessive time on root cause analysis during the incident
   • Demonstrated clear incident response process including communication, escalation, and coordination with other teams
   • Showed ability to make quick decisions with incomplete information while maintaining system stability
   • Followed up with proper post-incident analysis and prevention measures after the immediate crisis was resolved

   Likely follow-ups

   • How did you balance speed of resolution with thoroughness of the fix?
   • What did you learn from the post-mortem that changed how you approach incidents now?

   Company context

   DoorDash's 'Operate at Speed' principle is critical for SRE roles because the platform handles millions of real-time delivery requests daily. Downtime directly impacts Dasher earnings, merchant revenue, and consumer experience, requiring engineers to act decisively under pressure while maintaining high availability across the three-sided marketplace.

2. 2.Our Kafka clusters process millions of dispatch events per minute across DoorDash's real-time logistics platform. If you noticed consumer lag spiking during peak dinner hours, what would be your first three debugging steps?

   easy~3 min

   What interviewers look for

   • Checks consumer group metrics and partition assignment to identify if lag is isolated to specific partitions or consumers
   • Investigates broker health metrics including CPU, memory, disk I/O, and network to identify infrastructure bottlenecks
   • Reviews recent application deployments or configuration changes that could affect consumer processing speed
   • Considers the three-sided marketplace impact - how dispatch delays affect Dashers, merchants, and consumers simultaneously

   Likely follow-ups

   • How would you prioritize fixing consumer lag versus adding more partitions, given that this affects real-time Dasher assignments?
   • What monitoring alerts would you set up to catch this earlier, considering DoorDash's 'Operate at Speed' principle?

   Company context

   DoorDash's real-time dispatch system relies heavily on Kafka to coordinate millions of daily deliveries across their three-sided marketplace. Consumer lag directly impacts Dasher earnings, merchant order fulfillment, and consumer wait times, making fast diagnosis critical to the company's 'Operate at Speed' leadership principle and marketplace thinking.

3. 3.Design a feature flag system that serves DoorDash's microservices architecture during peak delivery hours when we're handling millions of requests per second. How would you ensure it stays available even when its own dependencies fail?

   easy~3 min

   What interviewers look for

   • Proposes local caching with stale-data fallback to prevent feature flag service outages from taking down core delivery flows
   • Designs for gradual rollout capabilities to safely deploy changes across DoorDash's three-sided marketplace without impacting all users simultaneously
   • Considers monitoring and alerting for flag evaluation latency and cache hit rates to maintain sub-second response times during peak hours

   Likely follow-ups

   • How would you handle a scenario where a new feature flag accidentally gets set to impact all Dashers during dinner rush?
   • Walk me through how you'd design the rollback mechanism if a feature flag change starts degrading order assignment latency.

   Company context

   DoorDash's real-time logistics platform requires feature flags that can handle massive scale while maintaining the reliability needed for time-sensitive delivery operations. Given DoorDash's 'Operate at Speed' principle, engineers need systems that enable rapid iteration without risking marketplace stability during peak hours when millions of orders are being processed.

4. 4.Tell me about a time you had to convince an engineering team to adopt a new operational practice or tool when they were resistant to the change. How did you approach it?

   easy~3 min

5. 5.DoorDash processes about 50 million orders per month. If we decided to add real-time order tracking photos from Dashers, estimate the storage costs and bandwidth implications. Walk me through your calculations.

   easy~4 min

6. 6.Tell me about a time you had to optimize system performance where improving one metric would negatively impact another metric. How did you approach the tradeoffs?

   medium~4 min

7. 7.You're designing monitoring for a new microservice that handles merchant onboarding workflows using Cadence. What metrics and alerts would you implement, and how would you balance noise versus catching real issues?

   medium~4 min

8. 8.DoorDash's driver mobile app needs to sync location updates from hundreds of thousands of active Dashers while maintaining accurate ETA predictions for consumers. Design the data pipeline and explain how you'd handle network partitions and mobile connectivity issues.

   medium~4 min

9. 9.Describe a situation where you had to balance the reliability needs of multiple teams or services with competing priorities. How did you decide what to focus on first?

   medium~4 min

10. 10.You notice that our Postgres read replicas in the West Coast region are showing 30% higher CPU utilization than usual, but no alerts have fired and application metrics look normal. How would you investigate this?

    medium~5 min

11. 11.Tell me about a specific time in the last year when you went significantly beyond your normal responsibilities to help a teammate or another team succeed. What was the situation and what did you do?

    hard~5 min

12. 12.DoorDash's dispatch service needs to handle 100k+ simultaneous Dasher location updates per second while maintaining sub-100ms latency for order assignments. Design the infrastructure architecture and explain your scaling strategy.

    hard~5 min

13. 13.Design a deployment system for DoorDash's Kotlin microservices that can safely roll out changes to services handling order dispatch without impacting active deliveries. The system needs to handle rollbacks within 60 seconds if issues are detected.

    hard~5 min

14. 14.Tell me about a time you had to lead a cross-functional effort to solve a complex operational problem that spanned multiple teams and systems. What was your approach to coordination and decision-making?

    hard~5 min

15. 15.DoorDash wants to expand internationally to a country with unreliable internet infrastructure where 40% of Dashers have intermittent connectivity. How would you design our dispatch system to handle this constraint while maintaining fair order distribution?

    hard~5 min