Caltech Bootcamp / Blog / /

The Top SQL Interview Questions for Data Engineers

SQL Interview Questions for Data engineers

Structured query language (or SQL for short) is a popular programming language for storing and processing information in relational databases. Many IT professionals, including data scientists and engineers, use it. Relational databases store information in tabular form, using rows and columns representing different data attributes and the many relationships between the data values. Professionals who work with data use SQL statements to search, store, update, remove, and retrieve information from the database. SQL is also used to maintain and optimize a database’s performance.

Data engineers work in different settings to develop systems that collect, manage, and convert raw data into usable information that business analysts and data scientists can interpret. The data engineer’s primary goal is to make the data accessible so organizations can use it to evaluate and optimize their performance. Through online data science training, aspiring data engineers can learn the required skills to perform these duties.

Moreover, before someone starts a job as a data engineer, they must ace their interview. This article helps you prepare for that interview by discussing a sample of the more popular SQL interview questions for data engineers. Data engineers primarily use SQL to create data integration scripts, execute analytical queries that change, and employ data for business insights. Data engineers use SQL to change databases and table structures, extracting data subsets from the database for different business analytics use cases.

The SQL interview questions for data engineers are broken down into beginner and experienced questions, a dozen of each. Let’s jump right in.

What Topics Are Typically Covered in SQL Interviews for Data Engineers?

Although no two companies interview SQL engineers the same, specific topics keep popping up. They are:

  • Database design. These questions cover your understanding of data architecture and design, including designing databases from scratch.
  • Definition-based SQL questions. These questions are short, basic SQL questions.
  • ETL SQL questions. ETL stands for extracting, transforming, and loading data, and these are frequently asked questions in data engineering interviews. Make sure you’re proficient in DDL and DML statements.
  • Reporting and metrics. Finally, these questions involve writing queries to pull metrics. Typically, these questions have a clearly defined metric to pull.

Now, let’s jump into the basic-level interview questions for data engineers.

SQL Interview Questions and Answers for Beginner Data Engineers

  1.     Why is SQL so popular?

SQL is a domain-specific language used to manage data in the Database Management System (DBMS). Since DBMS usage is prevalent, SQL skills are much in demand.

  1.     Name the five different SQL command types.

    The five types are:
  • Data Definition Language (DDL) Commands
  • Data Manipulation Language (DML) Commands
  • Data Control Language (DCL) Commands
  • Transaction Control Language (TCL) Commands
  • Data Query Language (DQL) Commands
  1.     How do you rank Data in SQL?

    Values are typically ranked using parameters such as sales and profits.
  2.     What are common table expressions in SQL?

    Common table expressions are used to simplify complex joins and run subqueries.
  3.     What’s the difference between SQL and MySQL?

SQL is a language; MySQL is a database management system.

  1.     What are the two types of database management systems?

The two types of database management systems are Relational Database Management Systems, where data is stored in relations (tables), such as MySQL, and Non-Relational Database Management Systems, such as MongoDB, which have no concept of relations, tuples, and attributes.

  1.     Explain the various SQL relationship types.
    The database relation types are:
  • One-to-one, where each record in one table corresponds to a maximum of one record in the other table.
  • One-to-many and many-to-one are the most frequent connections, and a record in one table is linked to more than one record in another.
  • Many-to-Many, which describes a relationship that requires multiple instances on each side.
  • Self-referencing relationships, when a table must declare a connection with itself.
  1.     What’s OLTP?

OLTP, short for online transactional processing, lets large groups of users execute massive amounts of real-time database transactions, typically through the Internet. Database transactions occur when the data in a database is queried, changed, inserted, or deleted.

  1.     What is OLAP, and how does it differ from OLTP?

OLAP is an acronym that stands for online analytical processing. While OLTP is an online database modification system, OLAP is an online database query response system.

  1. Explain tables and fields.

Tables are collections of data components in a relational database, organized in rows and columns. Records, or rows, are a single entry in a table. Tables consist of numerous records or rows, each of which can be further broken down into smaller units called Fields (or columns).

  1. What is a JOIN clause, and what are the different types?

A JOIN clause combines rows across at least two tables with a related column. The different types are:

  • (INNER) JOIN. This type returns the records with matching values in both tables.
  • LEFT (OUTER) JOIN. This type returns all the records from the left table with the corresponding matching records from the right table.
  • RIGHT (OUTER) JOIN. This clause type is the reverse of the previous one, returning all the records from the right table with their corresponding matching records from the left table.
  • FULL (OUTER) JOIN. This clause type returns all the records with a matching record in either left or right tables.
  1. What basic SQL-related skills should a SQL expert master?

    The basic SQL skills every good SQL expert should know are:
  • Database management
  • Structuring databases
  • Creating SQL clauses and statements
  • SQL System skills such as MYSQL and PostgreSQL
  • PHP expertise
  • Analyzing SQL data
  • Using WAMP with SQL to create a database
  • OLAP skills

Now that we have covered twelve of the most popular basic SQL engineer interview questions, let’s turn up the heat and tackle a dozen interview questions for experienced SQL data engineers.

SQL Interview Questions and Answers for Experienced Data Engineers

  1.     How would you prepare an SQL database for migration to a new server or a cloud-based service?

    Here are the steps to take:
  • Take the database through a dedupe process to eliminate extraneous data and guarantee data quality before starting the migration
  • Ensure the new server meets all technical requirements for the SQL database
  1.     What are the UNION, INTERSECT, and MINUS commands?
  • Union combines the results of two tables while eliminating duplicate entries
  • Intersect combines the results of both queries into one row
  • Minus returns a row from the first query but not from the second one
  1.     What is a schema in an SQL server?

Schema are lists of logical data structures, building and specifying the relationships among the database’s many entities. The term refers to the constraints that can be applied to a database and describes the various data kinds. A schema may also be used on Tables and Views. Schema comes in different shapes and sizes, with Star schema and Snowflake schema being two of the most popular.

  1.     How does a clustered index differ from a non-clustered index?

Clustered indexes modify how the user stores database records based on the indexed column and are helpful for fast data retrieval. On the other hand, non-clustered indexes create a different entity within the table, referencing the original table.

  1.     What is a foreign key?

A foreign key is a field or a group of several fields in one table that refers to a primary key in a different table. The table containing the foreign key is called the child table, while the table containing the primary key is the referenced or parent table.

  1.     What does normalization mean in the context of SQL?

Normalization minimizes database inconsistency, redundancy, and dependency by organizing the fields and tables. Normalization involves deleting, adding, or modifying fields that go into a single table.

  1.     Is a zero value or a blank space treated the same as NULL?

No. NULL is used when a value is absent, unavailable, unknown, unassigned, or inappropriate. Meanwhile, zero is a number, and blank spaces are considered characters.

  1.     When you modify a database, what statement does the system execute?

The system executes a trigger command whenever you modify the database.

  1.     And what’s a Trigger?

A trigger refers to a set of system catalog statements that runs whenever DML (or Data Manipulation Language) commands run on the system. The trigger is a special stored procedure called automatically in response to an event. The trigger command allows batch code execution whenever an update, insert, or delete command is executed for a specific table.

  1. What’s a SQL-stored procedure, and what’s it suitable for?

This is a precompiled set of SQL statements stored in a database, which can then be executed with a single command. These procedures are designed to improve performance, simplify complex SQL operations, and enhance security by letting administrators control access to sensitive database operations.

  1. What are aggregate functions in SQL? Give some examples of these functions.

In an aggregate function, values from multiple rows are merged to create a single value. AV, COUNT, MIN, MAX, and SUM are the most common aggregate functions.

  1.   Explain constraints.

Constraints are used to specify the limit on the table’s data type. Constraints can be specified when you create or alter the table statement. Constraint samples are:

  • NOT NULL
  • CHECK
  • DEFAULT
  • UNIQUE
  • PRIMARY KEY
  • FOREIGN KEY

How to Gain More Data Science Skills

While brushing up on the most-asked SQL interview questions for data engineers will undoubtedly help your chances, there’s nothing like getting more training and expanding your data science skill sets. This data science course teaches data science and generative AI skills via a high-engagement six-month learning experience that offers exposure to ChatGPT, DALL-E, Midjourney, and other vital tools.

And if you want to keep improving that skill set, try out this data science bootcamp that runs for 24 weeks and gives you valuable training in Generative AI, Prompt Engineering, ChatGPT, and much more.

According to Glassdoor.com, data engineers in the United States earn an average of $117,843 annually. So, boost those in-demand data science skills and get a career offering security, challenges, and fantastic compensation.

FAQ

How do you prepare for an SQL data engineer interview?

You prepare with one word: practice. Practice these tasks:

  • Design an ETL pipeline
  • Create, modify, and manage sample databases
  • Look up sample coding challenges in C++, Python, or Scala and try solving them
  • Learn what typical SQL interview questions to expect

What are the SQL skills for data engineers?

Data engineers must know how to pull data from diverse sources, change it into useful information, load it into practical formats, and send the results to the proper departments to make critical business decisions. Other necessary skills include aggregating data, filtering data, using subqueries, joining tables, and using window functions.

What does a data engineer do with SQL?

Data engineers typically use SQL to create data integration scripts, execute analytical queries that change, and employ data for business insights. Data engineers also use SQL to modify databases and table structures, pulling data subsets from the database for different business analytics use cases.

How do you crack an SQL interview?

Use these steps to crack an SQL interview:

  • Ask clarifying questions when the interviewer asks you a question
  • Identify the output’s relevant columns and focus solely on them
  • Think about what the final answer should look like
  • Break down problems into smaller parts and answer them one at a time
  • Include comments that explain each step that your query performs
  • Format your query for precision and neatness
  • Explain to the interviewer what you’re doing every step of the way

Data Science Bootcamp

Leave a Comment

Your email address will not be published.

Data Science in Finance

Technology at Work: Data Science in Finance

In today’s data-driven world, industries leverage advanced data analytics and AI-powered tools to improve services and their bottom line. The financial services industry is at the forefront of this innovation. This blog discusses data science in finance, including how companies use it, the skills required to leverage it, and more.

Components of Data Science

What Are the Components of Data Science?

Discover the core components of data science, from algorithms to tools and structures. Learn what makes data science work and how you can leverage this knowledge for your career.

Data Science Bootcamp

Duration

6 months

Learning Format

Online Bootcamp

Program Benefits