Paypal Interview Questions (13+ Questions)

Learn how to diagnose DNS resolver configurations across multiple sources on Linux using Bash commands. This guide covers examining /etc/resolv.conf, inspecting systemd-resolved settings, identifying symbolic links, and creating consolidated DNS diagnostics reports, essential for troubleshooting inconsistent domain resolution and split-horizon DNS issues.

Fix a crashing Pod by correctly configuring the Downward API to expose pod metadata as files accessible to the container.

Debug Gateway TLS issues: fix OpenSSL certificate generation with SAN, repair invalid secrets, and restore secure HTTPS traffic. Master K8s TLS configuration.

We have a deployment script that needs an API token to work. The problem here is that the workflow runs even when the token isn't configured, and the deployment fails silently in production. We need to add a validation step that checks if the secret is set before deploying and fails fast with a clea...

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We have two repositories, which is repo A and repo B. Repo A, which builds the pipeline, and repo B, which handles the deployment. We need to pass build metadata, specifically the image tag, from repo A to repo B using something called artifacts. This ensures repo B always deploys the exact version ...

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Scrape product data from an e-commerce website by parsing a product listing page and following links to individual product detail pages to extract and combine information using Python BeautifulSoup.

Snowflake is a cloud-based data warehouse platform. The syntax, the functions, the logic, everything is almost like in SQL. Our table, social media, contains information about different posts, its ID, text inside of it, date, amount of likes, comments, shares, and the name of the platform. Our job is simple. We go through every post and replace the word Python with PySpark. The only thing that is going to change is that inside of the text column, the word Python is replaced by PySpark. In Snowflake, it uses a dynamic reference with the ref function. Inside of the double curly braces, we put the ref function with the name of our table. Since our goal was to modify the text column, we need to use replace function here. Replace function takes three arguments: the string itself, the old value, and the new value. Replace basically scans through the string, finds the needed word Python, and swaps it with a new value.

This is a Snowflake question, which is a cloud-based data warehouse that uses SQL and all its main concepts. We are given three tables, products, sales, and inventory. All three tables are connected through product ID, since this is a common column. First, we need to calculate total quantity and total revenue per product from sales. Then we need to calculate total stock per product from inventory. And in the end, we need to join everything with products table, making sure every single product appears in the result, even if it has no sales or inventory records. If we try to join everything directly without aggregating first, we would get duplicate rows and completely wrong totals. A CTE, or in other words, a common table expression, is a temporary result set that we define at the top of our query. A left join keeps all rows from the left table, even if there is no matching row in the right table. The missing values just become null. Coalesce function takes a list of values and returns the first one that is not null.

Introduction

Mastering SQL queries is a vital skill for data professionals, and understanding how to extract meaningful insights from relational databases is a common topic in interviews. Below, we will explore an example of how to write an SQL query to determine the average order value for each...

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SELECT
account_id,
SUM(
CASE
WHEN transaction_type = 'deposit' THEN amount
WHEN transaction_type = 'withdrawal' THEN - amount
ELSE 0
END
) AS final_balance
FROM
transactions
GROUP BY
account_id
ORDER BY
account_id ASC;

def permute(nums: list[int]) -> list[list[int]]:
res = []

def dfs(current_perm):
    if len(current_perm) == len(nums):
        res.append(current_perm.copy())
        return
        
    for num in nums:
        if num in current_perm:
            continue
            
        current_perm.append(num)
        dfs(current_perm)
        current_perm.pop()
        
dfs([])
return res

def insert(intervals: list[list[int]], new_interval: list[int]) -> list[list[int]]:
res = []

for i in range(len(intervals)):
    if new_interval[1] < intervals[i][0]:
        res.append(new_interval)
        return res + intervals[i:]
    elif new_interval[0] > intervals[i][1]:
        res.append(intervals[i])
    else:
        new_interval = [
            min(new_interval[0], intervals[i][0]),
            max(new_interval[1], intervals[i][1])
        ]
        
res.append(new_interval)
return res

Objective

To solve the given SQL interview question, you need to write a query that calculates and ranks the profit margin percentages for each product. A profit margin percentage is calculated as ((selling_price - cost_price) / cost_price) * 100. The SQL query should retrieve the product name...

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