Business Intel Engineer, EU Customer Behavior and Marketing Analytics and Data Science

Amazon

There is a robot on an m x n grid. The robot is initially located at the top-left corner (i.e., grid0). The robot tries to move to the bottom-right corner (i.e., gridm - 1). The robot can only move either down or right at any point in time. Given the two integers m and n, return the number of possible unique paths that the robot can take to reach the bottom-right corner. The test cases are generated so that the answer will be less than or equal to 2 * 109. For example, if m = 3 and n = 7, the expected output is 28. Explain your approach, provide code, and analyze the time and space complexity. Also discuss edge cases and alternative solutions using combinatorics.

Amazon

Let's dive into a debugging scenario. Imagine you are working on a critical e-commerce platform used by millions of customers. During a peak shopping period (like Black Friday), you receive alerts indicating a significant slowdown in the checkout process. Customers are reporting that it takes an unusually long time to complete their purchases, and some are even experiencing transaction failures. This is directly impacting sales and customer satisfaction. Your team suspects a performance bottleneck somewhere in the system. The architecture involves multiple microservices, including a user authentication service, a product catalog service, an inventory service, a payment processing service, and an order management service. These services communicate with each other via REST APIs and message queues. The database consists of both relational (PostgreSQL) and NoSQL (Redis) databases. You have access to logging, monitoring tools (like Prometheus and Grafana), and distributed tracing (like Jaeger). How would you approach debugging this issue systematically, identify the root cause, and propose a solution? Be specific about the tools and techniques you would use at each stage. For example, walk me through what metrics you'd focus on, how you would narrow down the problematic service, and what steps you'd take to pinpoint the exact code or configuration causing the bottleneck. Provide specific examples of commands or queries you might use to gather data or test hypotheses. Also consider potential causes related to scaling, caching, database performance, and code inefficiencies. How would you ensure minimal disruption to the platform during the debugging process? How do you handle conflicting information or dead ends during debugging?

Amazon

Describe a time when a plan did not go as expected.