10 TE Connectivity SQL Interview Questions (Updated 2024)

Updated on

February 14, 2024

At TE Connectivity, SQL is used day-to-day for analyzing production efficiency data and for managing the extensive catalog of connectivity and sensor products. That's why TE Connectivity asks SQL coding questions in interviews for Data Analyst, Data Science, and BI jobs.

To help you prepare for the TE Connectivity SQL interview, this blog covers 10 TE Connectivity SQL interview questions – able to answer them all?

10 TE Connectivity SQL Interview Questions

SQL Question 1: Top Selling Products by Region

TE Connectivity, as a technology company, is keen on understanding their sales trends. They'd like you to write a SQL query using a window function to find out the top 3 selling products in each region for the last quarter.

Example Input:
Example Output:


This query first calculates the total units sold for each product by region. A window function () is used here to calculate the cumulative sum of sold units.

In the next step, another window function () is used to assign a row number to each row within a region based on the in descending order.

Finally, the query retrieves the top 3 products by total units sold for each region by filtering on .

To practice a similar window function question on DataLemur's free interactive SQL code editor, try this Google SQL Interview Question: Google SQL Interview Question

SQL Question 2: Calculate the Average Duration of Product Manufacturing

As a part of TE Connectivity, an industrial technology company, you are required to keep track of production durations for the different categories of products the company manufactures. Can you write a SQL query that calculates the average duration of manufacturing for each product category?

Example Input:
Example Output:
"Electrical"9.0 days
"Mechanical"8.5 days


The SQL statement performs the following:

  • The statement obtains the 'category' and the average duration of manufacturing calculated as the difference between 'end_date' and 'start_date'.
  • The function calculates the average of a set.
  • The clause groups the result set by 'category'.
  • Finally, the result displays the average manufacturing duration for each category of products that TE Connectivity manufactures.

To practice a very similar question try this interactive Tesla Unfinished Parts Question which is similar for calculating different stages of the manufacturing process or this Amazon Server Utilization Time Question which is similar for calculating durations using dates.

SQL Question 3: What is normalization?

Database normalization is the process of breaking down a table into smaller and more specific tables and defining relationships between them via foreign keys. This minimizes redundancy, and creates a database that's more flexible, scalable, and easier to maintain. It also helps to ensure the integrity of the data by minimizing the risk of data inconsistencies and anomalies.

TE Connectivity SQL Interview Questions

SQL Question 4: Calculate Click-Through-Rates for TE Connectivity's Products

TE Connectivity, a major manufacturer of electronic components, uses digital advertising to promote its various products. You're given two tables:

  1. - A record of all clicks on its digital ads with columns: , , , and .

  2. - A record of all purchases of its products with columns: , , , and .

Your task is to calculate the click-through-rate (the percentage of users seeing an advert and clicking on it) for each product, and then the conversion rate (the percentage of users who clicked on the ad and made a purchase). Assume that a purchase within an hour after a click is considered a conversion.

Example Input:
156306/01/2022 08:00:002001567
289106/10/2022 10:00:002002921
357706/18/2022 11:00:002003345
410106/22/2022 08:30:002004567
578107/05/2022 09:00:002005345
Example Input:
156306/01/2022 08:30:005671
289106/10/2022 11:00:009212
357706/18/2022 12:00:003451
410106/22/2022 10:00:005671


The solution is a two-step process. First, we calculate the total number of clicks (impressions) for each product. Then, in the second step, we try to find how many times those clicks lead to a purchase within next hour using INNER JOIN. In the end, we combine both data using LEFT JOIN to calculate the conversion rate (total_purchases / total_clicks).

Note: We're assuming that users cannot purchase without clicking. If they can, we'd need adjust the queries to account for that.

To practice a related problem on DataLemur's free online SQL code editor, solve this SQL interview question asked by Facebook: Facebook Click-through-rate SQL Question

SQL Question 5: What is a primary key?

A primary key is a special type of column or set of columns in a database table that is used to identify each row in the table. It helps to ensure that all the rows are distinct and prevents null values. Additionally, primary keys play a crucial role in maintaining the accuracy of the data by making sure that there are no duplicate rows. They are also used to establish relationships between tables.

To create a primary key in a SQL database, you can use the constraint. For example, in the table , the column is the primary key.

SQL Question 6: Calculate the Maximum Sales for Each Product Type in Each Quarter.

TE Connectivity, a technology company, produces different types of connectors. Each connector has a product type and is sold multiple times throughout the year. The company needs to calculate the maximum number of units sold for each product type in each quarter to better understand the demand pattern.

Given the table:

Example Input:
101'Type A'02/15/2021150
102'Type B'03/25/2021200
103'Type B'01/11/2021110
104'Type A'04/22/2021160
105'Type A'05/13/2021140
106'Type B'07/03/2021230
107'Type A'08/02/2021150
108'Type B'09/17/2021180
109'Type A'12/10/2021200
110'Type B'11/05/2021220

Write an SQL query to determine the maximum number of units sold for each product type in each quarter of the year.

Example Output:
'Type A'1150
'Type B'1200
'Type A'2160
'Type B'2230
'Type A'3150
'Type B'3180
'Type A'4200
'Type B'4220


This query extracts the quarter from sale_date and then groups the sales records by product_type and quarter. It aggregates the units_sold field using the MAX function to find the maximum sales volume for each product type in each quarter. The output is sorted by product_type and quarter to make it easier to interpret.

SQL Question 7: Can you explain the distinction between cross join and natural join?

A cross join is a type of JOIN operation in SQL that creates a new table by combining each row from the first table with every row from the second table. It is also known as a cartesian join.

For example, say you worked on the Marketing Analytics team at TE Connectivity, and needed to understand what advertising copy (text) goes best with what advertising creative (the photo that gets posted with the advertisement copy).

Here is an example of a cross-join between a table of ad_copy and a table of ad_creative:

A natural join, on the other hand, is a type of JOIN that combines rows from two or more tables based on their common columns. It is called a "natural" join because it is based on the natural relationship that exists between the common columns in the tables being joined.

For an example of each one, say you had sales data exported from TE Connectivity's Salesforce CRM stored in a datawarehouse which had two tables: and .

An (which is a type of natural join) combines the two tables on the common

This query will return rows from the sales and tables that have matching customer id values. Only rows with matching values will be included in the results.

One main difference between cross joins and natural joins is that cross joins do not require any common columns between the tables being joined, while natural joins do. Another difference is that cross joins can create very large tables if the input tables have a large number of rows, while natural joins will only return a table with the number of rows equal to the number of matching rows in the input tables.

SQL Question 8: Filtering Customer Records with Specific Patterns

You are a Database Administrator at TE Connectivity and your task is to filter out all customer records where the email addresses are from Gmail. Using the SQL keyword LIKE, how would you write a query to extract this data from the given table?

Example Input:


Example Output:

This query works by using the LIKE keyword in PostgreSQL to match text values against a pattern. The percent sign "%" is a wildcard character that matches any sequence of characters. In this case, the query will find all customer records where the email field ends with "@gmail.com", indicating that the customer uses a Gmail account. This can be very useful in filtering records based on specific text patterns.

SQL Question 9: Calculating Product Voltage Power Usage

TE Connectivity produces a wide range of electronic products. One essential information for their clients is knowing how much voltage each item consumes on average per hour. The data scientists are given product usage details that capture the voltage usage per minute along with the product's working hour per day. Your task is to create a SQL query that calculates the total power (which is voltage times working hours) consumption for each product, rounds to the nearest whole number and then finds the square root of this total power. The final output should also be rounded to the 2nd decimal point.

The 'products' table provides the average voltage consumed per minute (avg_voltage_per_min) and the average working hours per day (avg_work_hr_per_day).

Sample Input:
1Product A0.0358
2Product B0.0786
3Product C0.05612
Example Output:
1Product A107.37
2Product B107.37
3Product C214.74


Below is the PostgreSQL query:

In this SQL query, we first calculate the total power (voltage * working hours) for each product using a subquery. We multiply the average voltage per minute by 60 to get the voltage per hour, and then multiply by the average working hour per day. That gives us the total power usage for each product per day. Later, we apply the square root function (SQRT) to this total power, and then round this result to the 2nd decimal point.

To practice a very similar question try this interactive Amazon Server Utilization Time Question which is similar for calculating the total usage of a resource or this Microsoft Supercloud Customer Question which is similar for analyzing product usage data.

SQL Question 10: What does the function do, and when would you use it?

The COALESCE() function can be used to replace NULL values with a specified value. For instance, if you are a Data Analyst at a company and are working on a customer analytics project to identify the most engaged customers, you may have access to the following data in the table:


Before you could procede with your analysis, you would need to remove the NULLs, and replace them with the default value for email engagement (not_active), and the default sms_engagement level (not_opted_in).

To do this, you'd run the following query:

This would get you the following output:


Preparing For The TE Connectivity SQL Interview

The key to acing a TE Connectivity SQL interview is to practice, practice, and then practice some more! Beyond just solving the earlier TE Connectivity SQL interview questions, you should also solve the 200+ DataLemur SQL Interview Questions which come from companies like Microsoft, Google, and Facebook. DataLemur Questions

Each SQL question has multiple hints, step-by-step solutions and best of all, there is an online SQL coding environment so you can right in the browser run your query and have it graded.

To prep for the TE Connectivity SQL interview it is also wise to solve SQL questions from other tech companies like:

In case your SQL coding skills are weak, don't worry about going right into solving questions – refresh your SQL knowledge with this interactive SQL tutorial.

SQL tutorial for Data Scientists & Analysts

This tutorial covers SQL topics like handling dates and using ORDER BY – both of these pop up routinely during SQL job interviews at TE Connectivity.

TE Connectivity Data Science Interview Tips

What Do TE Connectivity Data Science Interviews Cover?

In addition to SQL query questions, the other question categories to practice for the TE Connectivity Data Science Interview are:

TE Connectivity Data Scientist

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