Build a scalable Data Pipeline Pipeline
Last updated: June 8, 2026
Quick Overview
Design a scalable data pipeline system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
DoorDash
June 8, 202619
15
3,561 solved
Design a scalable data pipeline system that handles millions of requests. Discuss trade-offs in consistency, availability, and performance.
This is a common system design question asked during Onsite at DoorDash. The interviewer expects you to demonstrate your ability to design large-scale distributed systems, make well-reasoned trade-offs, and communicate your thought process clearly. DoorDash values engineers who can think about scalability from day one.
What the Interviewer Expects
- Systematically gather requirements and estimate capacity (QPS, storage, bandwidth)
- Design a scalable architecture with clear component responsibilities
- Make well-reasoned database and caching decisions with trade-off analysis
- Address consistency vs availability trade-offs specific to the use case
- Discuss partitioning strategy, replication, and data modeling
- Cover failure handling, monitoring, and alerting strategies
Key Topics to Cover
How to Approach This
- Start by clarifying functional and non-functional requirements with the interviewer.
- Estimate the scale: QPS, storage, bandwidth. This drives your design decisions.
- Draw a high-level architecture first, then deep dive into 1-2 critical components.
- Discuss trade-offs explicitly (e.g., consistency vs availability, SQL vs NoSQL).
- Address failure scenarios, monitoring, and how the system handles 10x traffic spikes.
Possible Follow-up Questions
- How would you implement rate limiting to protect the system?
- How would you migrate from a monolithic to a microservices architecture?
- How would you handle schema migrations with zero downtime?
- How would you optimize costs as the system scales?
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Requirements
- Functional Requirements:
- Ingest real-time order data from various sources (e.g., restaurants, delivery partners).
- Process and transform data for analytics and reporting.
- Provide an A...
Capacity Estimation
- Estimating QPS:
- If there are 10 million requests per day, this translates to approximately 115 requests per second (QPS).
- Peak hours might see a spike; assuming 30% of requests happen du...
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