Prepare for and practice interview questions from Square across topics like SQL, Python, Product Metrics and more.

Square Interview Questions

A/B Testing

Algorithms

Analytics

Machine Learning

Probability

Product Metrics

Python

Statistics

Square Interview Guides

You’re tasked with designing a database system for Swipe Inc., a company that manages payments for software developers. Swipe manages a set of APIs so developers can abstract payment processes for their web service and transfer control over to Swipe’s APIs to manage payment security and finance handling (contacting credit card providers, etc.)

Your database system should store a collection of API keys with their attributes, as shown in the example below:

<pre tabindex="0" class="chroma"><code>{
 &#34;API_key&#34;:{
 &#34;Transaction_list&#34;:{
 &#34;User_ID&#34;:{
 &#34;Name&#34;:{
 &#34;f_name&#34;: 
 &#34;l_name&#34;: 
 }
 &#34;Card_Details&#34;:{
 &#34;Bank&#34;:
 &#34;Card_No&#34;:
 &#34;Expiry&#34;:
 &#34;CV&#34;:
 } 
 }
 }
 &#34;Curr_balance&#34;:
 }
}
</code></pre>

What are the functional and non-functional requirements for this database?

Determine the requirements for designing a database system to store payment APIs

Swipe Payment API

Let’s say you work for a financial company. You notice that the credit card payment amount per transaction has decreased.

How would you investigate what happened?

You notice that the credit card payment amount per transaction has decreased. How would you investigate what happened?

Decreasing Payments

Given the two tables, write a SQL query that creates a cumulative distribution of the number of comments per user. Assume bin buckets class intervals of one.

Example:

Input:

<code>users</code> table

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>

<tr>
<td><code>neighborhood_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>sex</code></td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>
<code>comments</code> table

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>user_id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>body</code></td>
<td>VARCHAR</td>
</tr>

<tr>
<td><code>created_at</code></td>
<td>DATETIME</td>
</tr>
</tbody>
</table>
Output:

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>frequency</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>cum_total</code></td>
<td>FLOAT</td>
</tr>
</tbody>
</table>

Square Interview Questions

Square Interview Guides

Square Interview Questions

Square Salaries by Position