Cracking the Data Engineering Interview

Name: Cracking the Data Engineering Interview
Rating: 4.4 (17 reviews)

Use SQL, Python, Data Modelling and Project Interview preparation to land your first job in Data Engineering!

Created byMilo Kite

Last updated 9/2024

English

What you'll learn

To query Data in a Database
To write your own scripts in Python
The most powerful SQL transformations
Python's control flow and conditional logic
To sell your project experience effectively
To navigate AI's role in Data
Strategies for modelling Data in a Database
How problems are posed in industry
Navigate live-coding interviews calmly
Write scalable, professional code
Know what role a Data Engineer performs
Gain confidence in yourself and experience
Set Theory's relation to Data
What hiring managers really look for

Course content

5 sections • 102 lectures • 3h 55m total length

Course Overview1:17
An introduction to what we'll learn about in the course and who the course is designed for.
Who am I?0:32
An understanding of my academic and employment history that relates to Data Engineering.
Why make this course?1:01
Why I believe that this course can be useful for you!
Course Content0:49
Explanation of the four chapters and how they'll help you.
Required Knowledge1:19
All prior knowledge needed to complete the course (Hint: it's not a lot).
What is a Data Engineer?2:39
An explanation of what data is and what function a Data Engineer forms in a modern enterprise.
Why be a Data Engineer?2:15
Motivation for why you should become a Data Engineer!

What is Data Modelling?2:35
Introduction and Overview of Data Modelling section.
What is the Data Modelling Interview?1:34
An explanation of the two possible formats a Data Modelling interview can form.
Keys and Data Models2:57
A quick understanding of Primary Keys and levels of Data Model.
Facts vs. Dimension Tables3:07
An explanation of the two different types of tables used in Data Modelling.
Normalisation4:04
How to normalise a Database through examples.
The Entity-Relationship Diagram3:11
How to visualise your database designs through diagrams.
Star vs. Snowflake Schema3:38
An explanation of the two most common Data Modelling strategies and their pros and cons.
Star vs. Snowflake Schema: Example1:21
An example of Star and Snowflake Schemas to help your understanding.
Slowly Changing Dimensions2:13
An advanced Data Modelling strategy to handle infrequently changing data.
Indexing4:13
An advanced Data Modelling strategy to improve the speed of data retreival.
Continue your Journey2:54
Resources for how to continue your learning journey.
Test your Knowledge on Data Modelling

Course Contents0:43
Introduction and Overview for SQL Mastery.
What is a Database?4:49
An explanation of a Database and how Data Engineers interact with them.
Data Warehouse analogy1:36
Comparing Databases to Warehouses to help reinforce your understanding of how we use Databases in enterprises.
What is SQL?2:45
An overview of the programming language SQL and what it is used for.
What is the SQL interview?1:25
An understanding of the format of the SQL interview and what can make you stand out.
Coding section format0:36
Outlining the format and resources of the coding section of the SQL course.
Creating an Account0:56
How to create an account on sqliteonline.com so we can practise our coding skills.
UI Explanation0:38
A quick run through of the user interface so we know how to use sqliteonline.com.
How to create your Database1:15
How to create your Database on sqliteonline.com
Select2:22
How to select Data from your Database.
Selecting: Practice
Data Types2:13
An understanding of floats, integers, strings, booleans, dates, and datetimes and how they are used in SQL.
Selecting and Filtering2:40
How to filter your tables to only rows you are interested in.
Selecting and Filtering: Example0:41
An example of filtering tables to help your understanding.
Selecting and Filtering: Practice
Ordering2:37
How to order your table rows in a way that makes sense to you.
Ordering: Example0:44
An example of ordering your table to help your understanding.
Ordering: Practice
Selecting and Filtering on multiple conditions1:44
How to filter your table rows on on any combination of conditions you require.
Selecting and Filtering on multiple conditions: Example0:53
An example of filtering on multiple conditions to help your understanding.
Selecting and Filtering on multiple conditions: Practice
Ordering and Filtering: Example1:39
Combining filtering and ordering your table through an example to help your understanding.
Ordering and Filtering: Practice
Limiting1:01
How to limit the number of rows in your table using a numerical cap.
Limiting: Example0:26
An example of limiting your table to help your understanding.
Limiting: Practice
Limiting and Ordering: Example1:24
Combining limiting and ordering your table through an example to help your understanding.
Limiting and Ordering: Practice
Advanced Filtering using Like3:10
How to improve your filtering using string conditions using regular expression pattern matching.
Advanced Filtering using Like: Example1:08
An example of using like to filter your table to help your understanding.
Advanced Filtering using Like: Practice
Aggregations3:25
How to aggregate your data and create summary statistics.
Aggregations: Example1:43
An example of aggregating your table to help your understanding.
Aggregations: Practice
Filtering on Aggregations2:01
How to filter your aggregated table on an aggregated field.
Filtering on Aggregations: Example1:33
An example of filtering on your aggregated fields to help your understanding.
Filtering on Aggregations: Practice
Joining Theory3:19
A theoretical explanation of how joins can be used to combine rows from multiple tables into one row.
Joining Tables3:47
A practical explanation of how joins can be used to combine rows from multiple tables into one row.
Joining: Practice
Case Statements4:04
How to create fields using custom conditional logic.
Case Statements: Example2:28
An example of using a case statement to help your understanding.
Case Statements: Practice
Set Operations4:21
Explaining how we can use set theory to combine tables or filter them.
Set Operations: Example1:31
An example of how set operations can be used to help your understanding.
Set Operations: Practice
Formatting SQL commands5:08
Using Common Table Expressions and Aliases to increase the complexity of our SQL commands whilst keeping them readable.
SQL Strategy2:56
Your SQL strategy to ensure you pass the interview with ease.
Continue your Journey1:35
Resources to continue your learning journey.

What is the Projects Interview?2:29
An understanding of what the Projects Interview could include.
Stack Alignment2:27
How to ensure you're knowledgeable on the technologies that your company uses.
Engineering Practices3:18
How to ensure you embody engineering ideals that allow your work to scale.
Engineering Practices: Example2:08
Using an employee from The Office as an example of how you can embody engineering values.
Engineering Practices: Strategy1:05
Your strategy for implementing our newfound knowledge of engineering practices.
Engineering Practices: Assignment
Interpersonal Skills2:41
How to show you can work efficiently within the team structure of modern enterprises.
First Impressions4:57
How to ensure you pass the very important vibe check with your interviewer!
Preparation1:32
Taking everything we've learned about into an actionable plan for selling your experience.

What is Python?1:05
An understanding about what a programming language is and what it's used for.
What is the Python Interview?1:24
Coding section format0:53
Outlining the format and resources of the coding section of the Python course.
Opening Notebook0:58
How to download our notebook we'll be doing exercises in and set it up in Google Colab.
Colab User Interface3:01
An explanation of how to navigate the Colab UI and run Python code within it.
Floats4:16
An introduction to our first numerical data types and how we can manipulate them.
Floats: Example1:42
An example problem with floats to help our understanding.
Floats: Practice
Integers1:54
An introduction to our second numerical data type and how we can manipulate them.
Integers: Example1:49
An example problem with integers to help our understanding.
Integers: Practice
Strings8:07
An introduction to our text-like data type and how we can manipulate them.
Strings: Example2:50
An example problem with strings to help our understanding.
Strings: Practice
Booleans4:11
An introduction to our true/false data type and how we can manipulate them.
Booleans: Example0:52
An example problem with booleans to help our understanding.
Booleans: Practice
Arithmetic3:19
A recap of our float and integer manipulation followed by more advanced mathematical operations.
Arithmetic: Example0:47
An example problem using arithmetic operations to help our understanding.
Arithmetic: Practice
Comparison Operators1:28
Learning about equality and inequalities within Python.
Comparison Operators: Example0:36
An example problem with comparison operators to help our understanding.
Logical Operators2:28
A recap of boolean manipulation followed by how we can combine boolean operators.
Logical Operators: Example0:33
An example problem with logical operators to help our understanding.
Assignment2:28
Explore Python assignment and incrementing, showing A = A + 1 and A += 1 to update values, and using times equals to scale numbers, with practical one-line updates.
Assignment: Example0:27
An example problem with assignment to help our understanding.
Lists7:05
An overview of a more complicated data type as well as common list methods and functions.
Lists: Example1:10
An example problem with lists to help our understanding.
Lists: Example 20:49
A second example problem with lists to help reinforce our understanding.
Lists: Practice
Tuples2:00
An overview of a more complicated data type that are very similar to lists.
Tuples: Example0:27
An example problem with tuples to help our understanding.
Tuples: Practice
Dictionaries5:13
Not to be confused with our A-Z friends, dictionaries in Python are used to assign values that can be accessed via keys.
Dictionaries: Example1:46
An example problem with dictionaries to help our understanding.
Dictionaries: Practice
Sets3:36
An overview of the set data type and operations we can use on them.
Sets: Example0:39
An example problem with sets to help our understanding.
Sets: Practice
Conditional Logic4:22
An explanation of how to implement if-else logic in Python.
Conditional Logic: Example3:03
An example problem with if-else logic to help our understanding.
Conditional Logic: Practice
While and For Loops8:32
A detailed explanation of how while and for loops can increase the complexity of your scripts.
For Loops: Example1:03
An example problem with for loops to help our understanding.
Loops: Practice
While Loops: Example2:17
An example problem with while loops to help our understanding.
While Loops: Practice
Advanced Loop Logic2:41
How to exit, skip and pass in loops.
Advanced Loop Logic: Example1:02
An example problem with break to help our understanding.
Advanced Loop Logic: Practice
Functions3:41
How to use functions within Python to format your code effectively.
Functions: Example1:12
An example problem with functions to help our understanding.
Functions: Practice
Continue Your Journey2:02
Continue your Python learning journey using these resources.

Requirements

No programming experience required, all you need is an email address and an internet connection. All of the tools used can be accessed from your browser.

Description

Ready to Launch Your Career in Data Engineering?
Whether you're curious about the world of data, a student, looking to change up your career, in a related field, or just looking to sharpen up your skills this course is designed just for you! Cracking the Data Engineering Interview is your gateway to landing a job in one of the fastest-growing, high-demand fields in tech today.

Course Overview

Cracking the Data Engineering Interview is a beginner-friendly course that takes you step-by-step through everything you need to succeed in your data engineering job hunt. We start with the basics and gradually build your skills, ensuring you’re fully equipped to crack any interview.

Throughout the course, you'll find loads of bite-sized coding example questions designed to test your skills and remove the scare factor. These exercises are not just practice—they’re a built-in study plan, helping you focus on key concepts without the extra effort of planning your own study sessions.

What this course DOESN'T include:

Downloading any software
Confusing terminology
Writing code in your terminal
Lengthy hard to digest lectures

Course Content

Introduction | We’ll kick off with an overview of the data engineering landscape, what the role entails, and why it’s such a critical function in the age of big data and AI.
Data Modelling | Learn the fundamentals of data modelling, including how to structure and organise data in ways that make it accessible, reliable, and easy to analyse.
SQL | SQL is the backbone of data engineering. In this module, you’ll master the art of writing efficient queries, understanding joins, and optimising databases. You’ll also get hands-on practice with exercises that mimic real-world scenarios you’ll face in a data engineering role.
Projects | This section also teaches you how to effectively present and sell your project experience to hiring managers. You'll learn how to highlight your contributions, explain the impact of your work, and showcase your skills in a way that makes you stand out in interviews.
Python | Python is a key tool in the data engineer’s toolkit. We’ll start from the basics and move into more advanced concepts like data manipulation, scripting, and automation.

Start Learning Today!

This course is structured to make learning easy and accessible, with no need for complex installations or deep technical know-how to get started. We believe that the best way to learn is by doing, and we’re here to support you every step of the way.

Get ready to ace your data engineering interview and step into a rewarding career with confidence. Enrol now and take the first step towards your new future!

If you have any questions about the content of the course or need any support during the course feel free to reach out to me by email.

Who this course is for:

This course is designed for programming beginners looking to get their first job in Data Engineering! The most common types are people looking for a career change, graduate students, professionals in related fields, or even Data Engineers looking to round out their experience.

Cracking the Data Engineering Interview

What you'll learn

Explore related topics

Course content

Introduction7 lectures • 10min

Data Modelling 10111 lectures • 32min

SQL Mastery36 lectures • 1hr 15min

Know your Projects8 lectures • 21min

Demystifying Python40 lectures • 1hr 38min

Requirements

Description

Who this course is for: