This is the code repository for Cracking the Data Engineering Interview, published by Packt.
Land your dream job with the help of resume-building tips, over 100 mock questions, and a unique portfolio
Preparing for a data engineering interview can often get overwhelming due to the abundance of tools and technologies, leaving you struggling to prioritize which ones to focus on. This hands-on guide provides you with the essential foundational and advanced knowledge needed to simplify your learning journey.
This book covers the following exciting features:
- Create maintainable and scalable code for unit testing
- Understand the fundamental concepts of core data engineering tasks
- Prepare with over 100 behavioral and technical interview questions
- Discover data engineer archetypes and how they can help you prepare for the interview
- Apply the essential concepts of Python and SQL in data engineering
- Build your personal brand to noticeably stand out as a candidate
If you feel this book is for you, get your copy today!
All of the code is organized into folders.
The code will look like the following:
from scrape import *
import pandas as pd
from sqlalchemy import create_engine
import psycopg2
Following is what you need for this book: If you’re an aspiring data engineer looking for guidance on how to land, prepare for, and excel in data engineering interviews, this book is for you. Familiarity with the fundamentals of data engineering, such as data modeling, cloud warehouses, programming (python and SQL), building data pipelines, scheduling your workflows (Airflow), and APIs, is a prerequisite.
With the following software and hardware list you can run all code files present in the book (Chapter 1-16).
| Chapter | Software required | OS required |
|---|---|---|
| 2 | Microsoft Azure | Windows, Mac OS X, and Linux (Any) |
| 2 | Amazon Web Services | Windows, Mac OS X, and Linux (Any) |
Kedeisha Bryan is a data professional with experience in data analytics, science, and engineering. She has prior experience combining both Six Sigma and analytics to provide data solutions that have impacted policy changes and leadership decisions. She is fluent in tools such as SQL, Python, and Tableau. She is the founder and leader at the Data in Motion Academy, providing personalized skill development, resources, and training at scale to aspiring data professionals across the globe. Her other works include another Packt book in the works and an SQL course for LinkedIn Learning.
Taamir Ransome is a Data Scientist and Software Engineer. He has experience in building machine learning and artificial intelligence solutions for the US Army. He is also the founder of the Vet Dev Institute, where he currently provides cloud-based data solutions for clients. He holds a master’s degree in Analytics from Western Governors University.