Business Intel Engineer, Grocery Data Tech Analytics

Amazon

Implement a Stack data structure using one or more Queues. Your stack should support the standard push, pop, top (peek), and empty operations. push(x):** Adds element x to the top of the stack. pop():** Removes the element on the top of the stack and returns it. top():** Returns the element on the top of the stack without removing it. empty():** Returns whether the stack is empty. For example, consider the following sequence of operations: push(1) push(2) top() // returns 2 pop() // returns 2 empty() // returns false Explain your approach clearly, focusing on how you would use queue operations (enqueue and dequeue) to achieve stack-like behavior. Discuss the time complexity of each operation in your implementation. Consider edge cases and potential optimizations.

Amazon

Let's explore scalability with a practical scenario. Imagine you're building a social media platform like Twitter, which needs to support millions of users who are constantly posting, liking, and re-sharing content. Consider these factors: Data Volume: Users generate terabytes of data daily. Read/Write Ratio: The platform experiences a high read-to-write ratio (many more reads than writes). Real-time Updates: Users expect to see new content and updates in real-time. Given these requirements, discuss the following: What are the key scalability challenges you anticipate? How would you approach scaling the platform's architecture to handle the increasing load, including database design, caching strategies, and load balancing? Describe specific technologies and techniques you might use to address each challenge. What are the trade-offs associated with different scaling approaches, and how would you evaluate the effectiveness of your scaling efforts?

Amazon

Tell me about a time you ran into a conflict with a project. How did you handle it?