Software Dev Engineer II, Tez

Amazon

Given a binary tree, find the lowest common ancestor (LCA) of two given nodes in the tree. According to the definition of LCA on Wikipedia: “The lowest common ancestor is defined between two nodes p and q as the lowest node in T that has both p and q as descendants (where we allow a node to be a descendant of itself). For example: If the tree is [3,5,1,6,2,0,8,null,null,7,4], p = 5, q = 1, then the expected output is 3, because the LCA of nodes 5 and 1 is 3. If the tree is [3,5,1,6,2,0,8,null,null,7,4], p = 5, q = 4, then the expected output is 5, because the LCA of nodes 5 and 4 is 5, since a node can be a descendant of itself according to the LCA definition. If the tree is [1,2], p = 1, q = 2, then the expected output is 1. Consider these constraints: The number of nodes in the tree is in the range [2, 10^5]. -10^9 <= Node.val <= 10^9 All Node.val are unique. p != q p and q will exist in the tree.

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 project that you're most proud of. To help me understand the scope and impact, please provide specific details about the project, including: The problem: What challenge were you trying to solve, and why was it important? Your role: What specific responsibilities did you have on the project? What were your key contributions? The technical details: What technologies, tools, or techniques did you use? For example, did you work with a specific programming language, framework, or database? The outcome: What were the results of the project? Did you meet the initial goals? Did you encounter any unexpected benefits or challenges? What did you learn?: Looking back, what would you do differently? What skills or knowledge did you gain from the experience? Did you face any setbacks, and how did you overcome them? For instance, if you worked on a project to improve the performance of a web application, you might discuss the specific performance bottlenecks you identified, the optimization techniques you implemented (e.g., caching, code optimization), and the resulting improvement in response time or throughput. Or, if you designed a new feature for a mobile app, you could describe the user research you conducted, the design process you followed, and the metrics you used to measure the feature's success. Be prepared to discuss technical challenges you faced and how you addressed them.