Consolidate and Rank Global Salaries in USD

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Q: What difficulty level is this coding question?

This is a Medium difficulty Data Manipulation (SQL/Python) question, commonly asked during Technical Screen rounds at Amazon.

Q: What role is this question designed for?

This question is commonly asked for Data Scientist candidates at Amazon during technical interviews.

Question

employees_us

+---------+----------+--------+---------+
| emp_id  | name     | salary | country |
+---------+----------+--------+---------+
| 1       | Alice    | 120000 | US      |
| 2       | Bob      | 95000  | US      |
| 3       | Carol    | 115000 | US      |

​

exchange_rates

+----------+----------+
| currency | usd_rate |
+----------+----------+
| USD      | 1.0      |
| EUR      | 1.12     |
| JPY      | 0.0091   |

##### Scenario

Global HR reporting: consolidate country files and rank worldwide salaries.

##### Question

Append several country-specific employee tables into a single global table. Using an exchange-rate reference table, find the top 10 salaries worldwide in USD.

##### Hints

Show UNION-ALL, JOIN with exchange rates, order by converted salary, and limit 10.

PracHub · Accepted Answer

This question evaluates data consolidation, currency normalization, and ranking competencies, measuring the ability to combine country-specific employee data and convert salaries into a common USD basis within the Data Manipulation (SQL/Python) domain.

Quick Overview

Consolidate and Rank Global Salaries in USD