11 Infineon SQL Interview Questions (Updated 2024)

Updated on

February 14, 2024

At Infineon, SQL is used quite frequently for extracting and analyzing manufacturing process data, and managing backend database for semiconductor design projects. Because of this, Infineon almost always evaluates jobseekers on SQL problems during interviews for Data Analytics, Data Science, and Data Engineering jobs.

To help you study for the Infineon SQL interview, this blog covers 11 Infineon SQL interview questions – able to answer them all?

11 Infineon SQL Interview Questions

SQL Question 1: Identify Frequent Purchasers in Infineon's Customers

Infineon is a company that deals with semiconductor solutions, microelectronics, and power management technology. Let's propose a scenario where Infineon wants to identify customers who made the most purchases over the past year (considered as 'power users'). They are specifically interested in the top 10 such users.

Assuming Infineon has a 'purchases' table that logs every single purchase, we will include some sample mock data to illustrate the concept.

Example Input:


The following SQL query would solve this problem:

This query first filters the 'purchases' table for entries within the specific date range we're interested in. It then groups the resulting rows by the user_id, and counts the number of rows (i.e., the number of purchases) for each user. The result is then sorted in descending order of num_purchases, after which we take the top 10 rows. This way we get to know the top 10 customers who made the most purchases in the year 2020.

To practice a related customer analytics question on DataLemur's free online SQL coding environment, try this Microsoft Teams Power User SQL Interview Question: Microsoft SQL Interview Question: Teams Super User

SQL Question 2: Calculating Average Score of Products

Consider that you are an analyst at Infineon and are tasked with evaluating the performance of various products based on customer reviews. Write a SQL query using window functions to calculate the average star rating of each product for each month. Note that 'stars' indicate the rating out of 5 that each user provided in the review.

Assume you have a table which contains the following data:

Example Input:
Example Output:


The script could be:

This query extracts the month from and groups by and the extracted month. It then calculates the average rating in each group. Finally, the result is ordered by and .

p.s. Window functions show up super frequently during SQL interviews, so practice the 27+ window function questions on DataLemur

SQL Interview Questions on DataLemur

SQL Question 3: What's the difference and a ?

No, in 99% of normal cases a and do NOT produce the same result.

You can think of more as set addition when it combines the results of two tables.

You can think of a more as set multiplication, producing all combos of table 1 with combos of table 2.

Infineon SQL Interview Questions

SQL Question 4: Analyze Product Sales for Infineon

Infineon is an enterprise dealing with electronics components sales. The components come from different manufacturers and are sold to various electronic manufacturing companies. The sales department would like to analyze the historical sales data they had collected over the past six months. They're particularly interested in understanding the total sales, in terms of quantity, for each product grouped by the manufacturer for a given month.

Design a database containing the necessary tables and relationships to model this information. Write an SQL query that can retrieve the total sales for each product grouped by manufacturer for May 2022.

Example Input:
1101Semiconductor A
2101Semiconductor B
3102Collector X
4102Collector Y
Example Input:
Example Input:


The SQL query in PostgreSQL will be as follows:

This query first restricts the records to May 2022 using the function and a WHERE clause. It then performs an inner join among the sales, products, and manufacturers tables based on the pre-defined foreign key relationships. This operation maps every product sold to its detailed product information and manufacturer. The query finally outputs the product's id, manufacturer's name, product's name and the total quantity sold grouped by the manufacturer and the product. The results are sorted in descending order according to the total sales.

SQL Question 5: What is the difference between a correlated subquery and non-correlated subquery?

A correlated sub-query is a sub-query that depends on the outer query and cannot be executed separately. It uses the outer query to filter or transform data by referencing a column from it, and the outer query uses the results of the inner query. In contrast, a non-correlated sub-query is independent of the outer query and can be executed on its own. It does not reference any columns from the outer query and is used to retrieve additional data needed by the outer query.

Here is an example of a correlated sub-query:

This query selects the and total sales of all Infineon customers in the sales table whose are greater than the average of their own customer group. The sub-query in this case is correlated with the outer query, as it references the column from the outer query ().

Here is an example of a non-correlated sub-query:

The sub-query in this case is non-correlated, as it does not reference any columns from the outer query.

Performance-wise, correlated sub-queries are generally slower to execute, as they have to be re-evaluated for each row of the outer query, while non-correlated sub-queries are faster, as they only have to be executed once.

SQL Question 6: Average Daily Power Consumption

Infineon is a company that deals with high-power semiconductors and solutions for efficient power conversion, transmission and generation. A relevant question for their business could be to find the average daily power consumption of different devices during a given month.

Consider the table that tracks the power consumed by different devices each day:

Example Input:

Your task is to write a SQL query that returns the average daily power consumption of each device for the month of


This query selects the and the average from the table for records between May 1, 2022 and May 31, 2022. It groups the result by , effectively computing the average daily power consumed by each device during the specified period.

To practice a very similar question try this interactive Google Odd and Even Measurements Question which is similar for daily consumption analysis or this Amazon Server Utilization Time Question which is similar for Daily Utilization Analysis.

SQL Question 7: How can you select records without duplicates from a table?

The clause in SQL allows you to select records that are unique, eliminating duplicates.

For example, if you had a table of Infineon employees, and wanted to see what are all the unique job titles that currently worked at the company, you could write the following query:

SQL Question 8: Identify Customers with 'New York' in their Address

Infineon wants to identify customers from their customer records whose address contains the string 'New York' for a targeted marketing campaign. Write an SQL query to do this.

Example Input:
101JohnDoejohn.doe@example.com1234 Broadway, New York, NY 10001
102JaneSmithjane.smith@example.com5678 Main St, Buffalo, NY 14201
103AliceJohnsonalice.johnson@example.com4321 Elm St, New York, NY 10002
104BobWilliamsbob.williams@example.com8765 Oak St, Albany, NY 12201
105CharlieBrowncharlie.brown@example.com1357 Pine St, New York, NY 10003
Example Output:
101JohnDoejohn.doe@example.com1234 Broadway, New York, NY 10001
103AliceJohnsonalice.johnson@example.com4321 Elm St, New York, NY 10002
105CharlieBrowncharlie.brown@example.com1357 Pine St, New York, NY 10003


This PostgreSQL query uses the LIKE keyword to filter for records in the table where the field contains the string 'New York'. The '%' character is a wildcard in SQL that matches any sequence of characters - so '%New York%' will match any address that contains 'New York' anywhere in the string.

SQL Question 9: Analyze Customer Purchase Patterns

You are tasked with analyzing customer purchase data for Infineon. In particular, you need to check for every customer to identify the products that have been purchased the most. We have the table which represents information about the customers of Infineon and the table that represents the transaction data.

The table is structured as follows:


The table is structured as follows:


For each customer, you need to identify the product they purchased the most (in terms of quantity). If a tie occurs, you can choose any of the products. If a customer hasn't purchased anything, they shouldn't appear in the result set. The result should be ordered by customer_id.


This query first calculates the total purchase quantity of each product for each customer by grouping the purchases table by both and summing the quantity ( subquery). Then it ranks the products by the total purchase quantity for each customer. In the outer query, it takes only the top-ranked (most purchased) product and orders the result by the customer ID. If there is a tie in quantity, any one of the products can appear in the result. This is done using the function which assigns the same rank to rows with the same quantity, so only one of them will be chosen by the outer query.

Since joins come up so often during SQL interviews, try this interactive Snapchat Join SQL question: Snapchat Join SQL question

SQL Question 10: What does it mean for a DBMS to enforce atomicity, consistency, isolation, and durability?

A DBMS (database management system), in order to ensure transactions are relaible and correct, tries to mantain the following ACID properties: Atomicity, Consistency, Isolation, and Durability

Here is what each of the ACID properties stands for:

Atomicity: ensures that a transaction is either completed in its entirety, or not completed at all. If a transaction fails halfway, the database does a rollback on the commit.

Consistency: ensures that a transaction will only be completed if adheres to the constraints defined in the database of the DB.

Isolation: ensures that concurrent transactions are isolated from each one another, so that the changes made by one transaction cannot be seen by a 2nd transaction until the 1st transaction is done.

**Durability: ** ensures that once a transaction has been committed, the database permanently stores the results in the DB.

As you can see, it's pretty important for Infineon's data systems to be ACID compliant, else they'll be a big problem for their customers!

SQL Question 11: Calculate Chip Performance Metrics

Infineon is a semiconductor company and measures chip performance on various metrics. One of the metrics is processing speed. However, the processing speed varies based on the temperature. The variance of speed from normal speed is captured in percentages under the name fluctuation. You are provided with chip_id, speed (in GHz), temperature (in °C) and fluctuation (%).

Your task is to calculate the actual speed at the given temperature. The actual speed can be calculated as speed + (speed * fluctuation/100).

Please note that fluctuation can be negative indicating speed is less than normal speed.

Also, for temperatures below 0 °C or above 30 °C, calculate the absolute value of fluctuation and update the actual speed. Use the ROUND function to round-off the actual speed to two decimal places.

Example Input:


This SQL query will calculate the actual speed based on given conditions. It will first check if the temperature is below 0 °C or above 30 °C. If it is, it takes the absolute value of fluctuation, otherwise it takes the original fluctuation. Then it calculates the actual_speed by adding the normal speed with the calculated (speed * fluctuation/100) and finally rounds it off to 2 decimal places. This will provide the expected output required for chip performance analysis.

To practice a very similar question try this interactive Google Odd and Even Measurements Question which is similar for requiring mathematical calculations on data or this Amazon Server Utilization Time Question which is similar for involving performance metrics calculations.

How To Prepare for the Infineon SQL Interview

The key to acing a Infineon SQL interview is to practice, practice, and then practice some more! Beyond just solving the earlier Infineon SQL interview questions, you should also solve the 200+ SQL Interview Questions on DataLemur which come from companies like FAANG tech companies and tech startups. DataLemur SQL and Data Science Interview Questions

Each problem on DataLemur has multiple hints, detailed solutions and crucially, there's an interactive coding environment so you can easily right in the browser your SQL query and have it checked.

To prep for the Infineon SQL interview it is also a great idea to solve SQL questions from other tech companies like:

However, if your SQL query skills are weak, forget about diving straight into solving questions – strengthen your SQL foundations with this SQL tutorial for Data Scientists & Analysts.

SQL tutorial for Data Analytics

This tutorial covers things like CASE/WHEN statements and inner vs. outer JOIN – both of which pop up often during SQL job interviews at Infineon.

Infineon Data Science Interview Tips

What Do Infineon Data Science Interviews Cover?

Besides SQL interview questions, the other question categories covered in the Infineon Data Science Interview are:

Infineon Data Scientist

How To Prepare for Infineon Data Science Interviews?

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

  • 201 Interview Questions from Google, Microsoft & tech startups
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  • Amazing Reviews (900+ 5-star reviews on Amazon)

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