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97 Things Every Data Engineer Should Know: Collective Wisdom from the Experts
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Take advantage of today's sky-high demand for data engineers. With this in-depth book, current and aspiring engineers will learn powerful real-world best practices for managing data big and small. Contributors from notable companies including Twitter, Google, Stitch Fix, Microsoft, Capital One, and LinkedIn share their experiences and lessons learned for overcoming a variety of specific and often nagging challenges.
Edited by Tobias Macey, host of the popular Data Engineering Podcast, this book presents 97 concise and useful tips for cleaning, prepping, wrangling, storing, processing, and ingesting data. Data engineers, data architects, data team managers, data scientists, machine learning engineers, and software engineers will greatly benefit from the wisdom and experience of their peers.
Topics include:
- The Importance of Data Lineage - Julien Le Dem
- Data Security for Data Engineers - Katharine Jarmul
- The Two Types of Data Engineering and Data Engineers - Jesse Anderson
- Six Dimensions for Picking an Analytical Data Warehouse - Gleb Mezhanskiy
- The End of ETL as We Know It - Paul Singman
- Building a Career as a Data Engineer - Vijay Kiran
- Modern Metadata for the Modern Data Stack - Prukalpa Sankar
- Your Data Tests Failed! Now What? - Sam Bail
- ISBN-101492062413
- ISBN-13978-1492062417
- Edition1st
- PublisherO'Reilly Media
- Publication dateJuly 20, 2021
- LanguageEnglish
- Dimensions5.75 x 0.5 x 8.75 inches
- Print length262 pages
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From the Publisher
From the Preface
Data engineering as a distinct role is relatively new, but the responsibilities have existed for decades. Broadly speaking, a data engineer makes data available for use in analytics, machine learning, business intelligence, etc. The introduction of big data technologies, data science, distributed computing, and the cloud have all contributed to making the work of the data engineer more necessary, more complex, and (paradoxically) more possible. It is an impossible task to write a single book that encompasses everything that you will need to know to be effective as a data engineer, but there are still a number of core principles that will help you in your journey.
This book is a collection of advice from a wide range of individuals who have learned valuable lessons about working with data the hard way.
To save you the work of making their same mistakes, we have collected their advice to give you a set of building blocks that can be used to lay your own foundation for a successful career in data engineering. In these pages you will find career tips for working in data teams, engineering advice for how to think about your tools, and fundamental principles of distributed systems.
There are many paths into data engineering, and no two people will use the same set of tools, but we hope that you will find the inspiration that will guide you on your journey. So regardless of whether this is your first step on the road, or you have been walking it for years we wish you the best of luck in your adventures.
Editorial Reviews
About the Author
Product details
- Publisher : O'Reilly Media
- Publication date : July 20, 2021
- Edition : 1st
- Language : English
- Print length : 262 pages
- ISBN-10 : 1492062413
- ISBN-13 : 978-1492062417
- Item Weight : 2.31 pounds
- Dimensions : 5.75 x 0.5 x 8.75 inches
- Best Sellers Rank: #1,365,696 in Books (See Top 100 in Books)
- #221 in Data Warehousing (Books)
- #461 in Data Mining (Books)
- #580 in Software Testing
- Customer Reviews:
About the authors

Tobias Macey hosts the Data Engineering Podcast and Podcast.__init__, where he discusses the tools, topics, and people that comprise the data engineering and Python communities, respectively. His experience across the domains of infrastructure, software, the cloud, and data engineering allows him to ask informed questions and bring useful context to the discussions. The ongoing focus of his career is to help educate people, through designing and building platforms that power online learning, consulting with companies and investors to understand the possibilities of emerging technologies, and leading teams of engineers to help them grow professionally.

Bas is an experienced ‘coding architect’ or ‘technology lead’. He helps organizations with big data and AI by building state-of-the-art solutions. Bas is an independent consultant and works from his own company Aizonic. He is a frequent speaker in tech conferences and meetup, and occasionally works as a teacher or coach.
















