- Trees and graph traversals – Handling hierarchical data structures, finding diameters, and calculating paths.
- Dynamic programming – Recognizing overlapping subproblems and formulating optimal substructures.
- Advanced concepts (less common) – Bit manipulation algorithms, segment trees, and advanced string matching heuristics.
Example questions or scenarios:
- "Given an array of integers, find the subset with a sum equal to k and optimize the space complexity."
- "Implement an algorithm to find the minimum number of edits required to convert one string into another."
System Design & Architecture
Designing robust, scalable systems that survive massive traffic surges.
This area evaluates your capacity to design distributed architectures that remain resilient under extreme load. Strong candidates demonstrate a clear methodology: clarifying functional and non-functional requirements, estimating scale, defining core APIs, sketching out data models, and addressing bottlenecks such as single points of failure, latency, and database contention.
Be ready to go over:
- Caching strategies – Implementing multi-tier caching, cache-aside patterns, and eviction policies like LRU.
- Load balancing and horizontal scaling – Distributing incoming traffic evenly across microservices.
- Database scaling – Sharding, partitioning, replication lag, and choosing between SQL and NoSQL stores.
- Advanced concepts (less common) – Distributed locking mechanisms, consensus algorithms like Raft, and event-driven architectures with Kafka.
Example questions or scenarios:
- "How would you design a real-time notification service that sends alerts to millions of users simultaneously?"
- "Discuss the database partitioning strategy for a high-write transactional ledger."
Database Internals & Storage
Understanding how data is stored, indexed, and retrieved efficiently.
Dream11 handles massive volumes of transactional and analytical data, making deep database knowledge crucial. Interviewers will test your understanding of what happens under the hood when a query executes, how indexes affect write performance, and how transaction isolation levels manage concurrent data access.
Be ready to go over:
- Indexing mechanisms – B-trees, composite indexes, and identifying query bottlenecks caused by improper indexing.
- ACID properties and isolation levels – Preventing dirty reads, non-repeatable reads, and phantom reads.
- Query optimization – Analyzing execution plans, joining large datasets, and refactoring expensive queries.
- Advanced concepts (less common) – Columnar storage formats, time-series data modeling, and database tuning at the OS level.
Example questions or scenarios:
- "Explain why adding an index on a datetime column might not solve a specific range query performance issue."
- "Walk me through how MVCC (Multi-Version Concurrency Control) works in relational databases."
Low-Level Design & Code Quality
Writing maintainable, extensible object-oriented code.
Low-level design rounds evaluate your ability to apply design patterns, write clean and testable code, and handle concurrency correctly. You will be given a problem statement, expected to discuss the class architecture and interfaces before coding, and evaluated on how well your code handles edge cases and thread safety.
Be ready to go over:
- Object-oriented design principles – SOLID principles, encapsulation, and domain modeling.
- Design patterns – Factory, Strategy, Observer, and Singleton patterns applied to practical problems.
- Concurrency and thread safety – Utilizing read-write locks, semaphores, and avoiding race conditions.
- Advanced concepts (less common) – Plugin architectures, reflection-based dependency injection, and custom memory management.
Example questions or scenarios:
- "Design a parking lot management system supporting multiple vehicle types and dynamic pricing tiers."
- "Identify and fix race conditions in a provided multi-threaded task scheduler snippet."
