11 Siltronic SQL Interview Questions (Updated 2024)

Updated on

March 3, 2024

At Siltronic, SQL is often used for analyzing semiconductor manufacturing data for quality control. That's the reason behind why Siltronic often tests SQL coding questions during interviews for Data Science and Data Engineering positions.

As such, to help you prepare for the Siltronic SQL interview, we've curated 11 Siltronic SQL interview questions – how many can you solve?

11 Siltronic SQL Interview Questions

SQL Question 1: Calculate Average Wafer Rejection Rate per Month

As a semiconductor company, Siltronic is heavily involved in the manufacturing of wafers. A useful piece of information might be the average rejection rate in their manufacturing process per month to monitor the quality of the production.

Example Input:

You are asked to calculate the average rejection rate per month. The rejection rate can be calculated using the formula: (rejected/total_produced)*100. Use PostgreSQL queries for this task.

Example Output:


This SQL query calculates the average wafer rejection rate for each month. It uses the PostgreSQL function to get the month part of the . The computation uses explicit casting to decimal to allow fractional values, then it calculates rejection rate, lastly it averages them for each group of months.

For more window function practice, solve this Uber SQL problem on DataLemur's online SQL code editor:

Uber Window Function SQL Interview Question

SQL Question 2: Production, Sales and Inventory management for Siltronic

Siltronic is a global leader in the market for hyperpure silicon wafers. The company would like to optimize its production, sales and inventory management process. Design a database to track the production, sales and inventory of different products and write a SQL query to fetch the details of the products that have less than the minimum threshold (20 units) in the inventory.

Consider the 3 tables below:

1001Hyperpure Silicon Wafer A40.50
1002Hyperpure Silicon Wafer B50.00
1003Hyperpure Silicon Wafer C45.25


This query first calculates the units in inventory for each product by subtracting the total units sold from the total units produced for the year 2022 (both operations are performed using subqueries on the and tables respectively). This is done in a Common Table Expression (CTE) called . The query then selects the products from this CTE that have less than 20 units left in the inventory.

SQL Question 3: What's the difference between an inner and a full outer join?

An inner join only includes rows from both tables that satisfy the join condition, whereas a full outer join includes all rows from both tables, regardless of whether they match the join condition or not.

To demonstrate each kind, Imagine you were working on a Advertising Analytics project at Siltronic and had two database tables: an table that contains data on Google Ads keywords and their bid amounts, and a table with information on product sales and the Google Ads keywords that drove those sales.

An retrieves rows from both tables where there is a match in the shared key or keys. For example, an INNER JOIN between the table and the table could be performed using the keyword column as the shared key. This would retrieve only the rows where the keyword in the table matches the keyword in the table.

A retrieves all rows from both tables, regardless of whether there is a match in the shared key or keys. If there is no match, values will be returned for the columns of the non-matching table.

Siltronic SQL Interview Questions

SQL Question 4: Filter Siltronic Customer Records

You've been provided with a database of Siltronic's customers. Your task is to write a SQL query that filters out customers based on the following conditions:

  1. They have ordered a product in the last 6 months.
  2. Their total spending during this period is more than $1000.
  3. The customers are not from Germany.
Example Input:
1John DoeUSA
2Jane SmithGermany
3Robert JohnsonCanada
Example Input:


This query first selects the customers who have placed an order in the last 6 months and their total spending during this period. The subquery then returns the customer_id and total spending. The main query then joins these results with the customer table based on customer_id. It filters out customers who have spent more than $1000 and are not from Germany.

SQL Question 5: What is a self-join?

A self-join is a type of JOIN where a table is joined to itself. To execute a self-join, you must include the table name twice in the FROM clause and assign a different alias to each instance. You can then join the two copies of the table using a JOIN clause, and use a WHERE clause to specify the relationship between the rows.

For example, say you had website visitor data for Siltronic, exported from the company's Google Analytics account. In support of the web-dev team, you had to analyze pairs of pages for UX or navigational issues. As part of that analysis, you wanted to generate all pairs of URLs, but needed to avoid pairs where both the URLs were the same since that's not a valid pair.

The self-join query would like the following:

This query returns the url of each page () along with the url of the page that referred to it (). The self-join is performed using the field, which specifies the id of the page that referred the visitor to the current page, and avoids any pages that referred themself (aka data anomalies).

SQL Question 6: Analyzing Click-Through Rates on Ads for Siltronic

Given a database with two tables, and , for the company Siltronic, write an SQL query to calculate the click-through conversion rate for each ad.

logs each time a person clicks on an ad, categorizing each ad by ad_id and recording the user_id and timestamp of the click. logs each time a user adds a product to their cart after clicking on the ad, also recording the ad_id, user_id and timestamp.

Example Input:
134507/19/2022 06:32:00
212407/19/2022 09:15:00
167807/20/2022 11:55:00
334507/20/2022 14:30:00
278907/21/2022 16:00:00
Example Input:
134507/19/2022 07:00:00
212407/19/2022 10:30:00
167807/20/2022 14:30:00
334507/21/2022 14:00:00


This SQL query first performs a LEFT JOIN on and on both and . Then, for each , it counts the distinct number of for both tables. The conversion rate is calculated as the number of unique users who added a product to the cart after clicking on the ad () over the total number of unique users who clicked on the ad (). To account for potential division by zero cases, we use function.

To solve a similar problem about calculating rates, solve this SQL interview question from TikTok within DataLemur's interactive coding environment: TikTok SQL question

SQL Question 7: What's the difference between and ?

The operator merges the output of two or more statements into a single result set. It ignores duplicated rows, and makes sure each row in the result set is unique.

For a concrete example, say you were a Data Analyst at Siltronic working on a Marketing Analytics project. If you needed to get the combined result set of both Siltronic's Google and Facebook ads you could execute this SQL query:

The operator works in a similar way to combine data from multiple statements, but it differs from the operator when it comes to handling duplicate rows. Whereas filters out duplicates (so if the same ad_name is run on both Facebook and Google, it only shows up once), outputs duplicate rows.

SQL Question 8: Calculate the Average Quantity of Each Product Sold Per Month

Siltronic is a manufacturer of semiconductor materials. Let's consider they operate with products of various types and they want to know on average, how many quantities of each product they sell per month. Write a SQL query to compute this average.

Example Input:
101200102/20/2022 00:00:00500
201200202/21/2022 00:00:00400
301200102/25/2022 00:00:00300
401200303/15/2022 00:00:00700
501200203/20/2022 00:00:00600
Example Output:


This query leverages the function to get the month of the sale_date, groups by it along with the product_id to get the average quantity sold each month for each product. The function is used to calculate the average quantity of each product sold per month. The statement is used to order the results by month and product_id for easier reading.

SQL Question 9: Join and Aggregate Data from and Tables

In the Siltronic database, we have a table and a table. They contain the following columns:

  • The table has columns customer_id, first_name, last_name, and email.
  • The table has columns purchase_id, product_id, quantity, customer_id, and purchase_date.

Write a SQL query to find out the total quantity of each product purchased by each customer. Consider only those customers who have a total purchase quantity across all products of more than 100 units.

Example Input:


Example Input:

1013017086706/08/2022 00:00:00
1023025053006/10/2022 00:00:00
1033016086706/10/2022 00:00:00
1043018053006/18/2022 00:00:00
1053039063107/26/2022 00:00:00

Example Output:



In this query, we're joining the and tables on the column. We're then grouping by , , and to find the total quantity of each product purchased by each customer. The clause filters out the results to only include those customers who have purchased more than 100 units in total.

Since joins come up routinely during SQL interviews, practice this interactive Snapchat SQL Interview question using JOINS: Snapchat Join SQL question

SQL Question 10: What's the difference between a left and right join?

In SQL, both a left and right join is used to combine rows from different tables based on a shared key or set of keys, resulting in a single merged table of data. However, here's the difference:

LEFT (OUTER) JOIN: Retrieves all the records/rows from the left and the matched records/rows from the right table.

RIGHT (OUTER) JOIN: Retrieves all the records/rows from the right and the matched records/rows from the left table.

SQL Question 11: Calculate Average Power Consumption

Siltronic is a company that manufactures wafers. Assume each wafer production process is uniquely identified by a and produces a certain in kwH. Power consumption varies due to the different kinds of wafers being produced and the machine calibration at the time of production.

The task is to write a PostgreSQL query that calculates the average power consumption for each wafer category. The wafer category is decided by taking the modulus 3 () of the . Round the average power consumption to the nearest 2 decimal places. Also, list the square root () of the maximum power consumption encountered in each category.

Example Input:

Example Output:



In this query, we are using the modulo operator to categorize our wafers. We then use the functions to perform mathematical calculations on the field to get our average power consumption per category and the square root of the maximum power consumption in each category respectively. This query then groups the results by the .

To practice a very similar question try this interactive Amazon Highest-Grossing Items Question which is similar for calculating metrics within categories or this Amazon Average Review Ratings Question which is similar for calculating averages grouped by unique items.

How To Prepare for the Siltronic SQL Interview

Assuming that you've already got basic SQL skills, the next best tip we have to prepare for the Siltronic SQL interview is to solve as many practice SQL interview questions as you can! In addition to solving the above Siltronic SQL interview questions, you should also solve the 200+ SQL questions on DataLemur which come from companies like Netflix, Airbnb, and Amazon. DataLemur Question Bank

Each problem on DataLemur has hints to guide you, detailed solutions and most importantly, there is an interactive coding environment so you can right online code up your query and have it checked.

To prep for the Siltronic SQL interview you can also be wise to practice SQL questions from other tech companies like:

But if your SQL coding skills are weak, forget about diving straight into solving questions – refresh your SQL knowledge with this DataLemur SQL Tutorial.

DataLemur SQL Course

This tutorial covers things like filtering on multiple conditions using AND/OR/NOT and inner vs. outer JOIN – both of which show up frequently in Siltronic SQL assessments.

Siltronic Data Science Interview Tips

What Do Siltronic Data Science Interviews Cover?

In addition to SQL interview questions, the other types of questions to practice for the Siltronic Data Science Interview are:

Siltronic Data Scientist

How To Prepare for Siltronic Data Science Interviews?

The best way to prepare for Siltronic Data Science interviews is by reading Ace the Data Science Interview. The book's got:

  • 201 Interview Questions from FAANG & startups
  • A Crash Course on Product Analytics, SQL & ML
  • Amazing Reviews (900+ reviews, 4.5-star rating)

Acing Data Science Interview