Toast India Backend Engineer Interview: Rounds, Questions and Preparation

What the job involves

Backend engineers at global tech companies like Toast India build and maintain server-side systems that power restaurant point-of-sale platforms, payment processing, and order management. They design APIs, optimize databases, and ensure high availability for millions of transactions daily. The role involves close collaboration with frontend, mobile, and data teams to deliver reliable, scalable services.

Role and Technical Knowledge

1. 1

   Explain how you would design a REST API for a restaurant menu management system.

   Cover resource modeling (menus, items, categories), HTTP methods, status codes, and versioning. Mention pagination and authentication.

2. 2

   What is database indexing and how does it improve query performance in a high-traffic POS system?

   Explain B-tree indexes, trade-offs of over-indexing, and how indexes speed up reads but slow writes. Relate to frequent order lookups.

3. 3

   How would you handle concurrency when multiple waiters update the same table's order simultaneously?

   Discuss optimistic vs pessimistic locking, database transactions, and idempotency. Mention using version numbers or timestamps.

4. 4

   Describe the difference between SQL and NoSQL databases and when you would choose each for a payment processing backend.

   Highlight ACID compliance in SQL for transactions, and scalability of NoSQL for logs or session data. Give examples like PostgreSQL vs Cassandra.

Practical Scenarios

1. 5

   A payment service is experiencing intermittent timeouts during peak lunch hours. How would you debug and resolve this?

   Outline steps: check logs and metrics, identify bottlenecks (DB, network, CPU), scale horizontally, add caching, and implement circuit breakers.

2. 6

   You need to add a new feature to an existing API without breaking current clients. How do you approach it?

   Discuss API versioning, backward compatibility, feature flags, and gradual rollout. Mention contract testing.

3. 7

   How would you ensure data consistency between a POS terminal and a cloud backend when network connectivity is unreliable?

   Cover offline-first design, conflict resolution (last-write-wins or CRDTs), sync queues, and idempotent operations.

4. 8

   Your team needs to reduce the latency of an order retrieval endpoint from 500ms to under 100ms. What steps would you take?

   Suggest profiling, adding indexes, caching frequent queries, denormalizing data, and using read replicas.

Behavioural and HR

1. 9

   Tell me about a time you had to learn a new technology quickly for a project. How did you approach it?

   Use STAR method: describe the situation, your learning strategy (docs, tutorials, mentorship), and the outcome. Show adaptability.

2. 10

   Describe a situation where you disagreed with a teammate on a technical decision. How did you resolve it?

   Focus on respectful communication, data-driven arguments, and willingness to compromise. Highlight the final solution and team harmony.

3. 11

   Why do you want to work as a backend engineer in the restaurant tech sector, and why our company?

   Connect personal interest in scalable systems and food tech. Mention company's product impact, culture, and learning opportunities.

4. 12

   How do you prioritize tasks when you have multiple deadlines and production issues?

   Explain using urgency vs importance, communicating with stakeholders, and documenting progress. Give an example from internships or projects.

Problem Solving and Coding

1. 13

   Given a stream of orders with timestamps, write a function to find the busiest hour of the day.

   Discuss sliding window or hashmap counting. Consider time zones and edge cases like empty input.

2. 14

   How would you detect and prevent duplicate payment transactions in a distributed system?

   Mention idempotency keys, unique constraints, and distributed locks. Explain how to handle retries safely.

3. 15

   Implement a rate limiter for an API endpoint that allows 100 requests per minute per user.

   Use token bucket or sliding window algorithm. Discuss in-memory vs distributed (Redis) implementation.

4. 16

   Write a SQL query to find the top 5 most ordered menu items in the last week.

   Use GROUP BY, COUNT, and date filtering. Mention indexing on order date and item ID for performance.