Data Engineer Career Path & Resources
Data is the fuel of the modern economy and Data Engineers provide the necessary knowledge to extract as much knowledge out of it as possible – a key role!
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Why should you become a
Data Engineer?
If 'data is the new oil' then data engineers are the equivalent of refineries which turn crude raw oil into usable forms like petrol and other forms of fuel. A key role in the modern economy in a wide variety of businesses, from startups to big tech. This shows in the meteoric growth of data engineering roles and the salaries that are shooting up to new heights.
The best part – other than data scientists, data engineering career paths are more accessible. Strong communication and being a team player is as important – if not more – compared to the ability to crunch some data.
Best books to build Data Engineering understanding.
A well-written and thorough book can be an amazing path to build deeper understanding and also act as a
handbook as you discover the internet's vast resources.
These are our and our experts top picks to get
started building career-relevant skills.
Data Engineering Cookbook
Five types of content are in this book: Articles the author wrote, links to his podcast episodes (video & audio), more than 200 links to helpful websites he like, data engineering interview questions and case studies.
The Data Warehouse Toolkit
One of the most dramatic new developments in database design, the dimensional data warehouse is a powerful database model that.significantly enhances managers' ability to quickly analyze large, multidimensional data sets. Written by the leading proponent of this revolutionary new approach, this valuable book/CD toolkit outfits you with all the nuts-and-bolts information you need to design, build, manage, and use dimensional data warehouses for virtually any type of business application, as well as software for querying dimensional data warehouses.
Big Data
Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they're built.
Data Pipelines Pocket Reference
Data pipelines are the foundation for success in data analytics. Moving data from numerous diverse sources and transforming it to provide context is the difference between having data and actually gaining value from it. This pocket reference defines data pipelines and explains how they work in today's modern data stack.
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Courses to deepen your Data Engineering skills.
These days, courses are no longer a sequence of videos. They are usually accompanied by projects and a
learning community, keeping you accountable and on the path.
Our experts recommend these courses, from free
selections to paid programs.
Data Engineering Foundations
Build the Foundation for a Data Engineering Career. Develop hands-on experience with Python, SQL, and Relational Databases and master the fundamentals of the Data Engineering ecosystem.
Data Engineering
Learn to design data models, build data warehouses and data lakes, automate data pipelines, and work with massive datasets. At the end of the program, you’ll combine your new skills by completing a capstone project.
Introduction to Data Engineering
Learn about the world of data engineering with an overview of all its relevant topics and tools!
Data Engineering Career Path
Data engineering has seen explosive growth recently as more industries depend on data to drive key business decisions. Take advantage of the surge in demand by becoming a data engineer with Dataquest.
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The Data Engineering must-reads you shouldn't miss.
Key articles and posts of industry experts can help you get a better picture of what you are getting
into.
In our opinion, these are some must-reads you really shouldn't miss.
The Path to Becoming a Data Engineer
The definitive guide to help you become a data engineer.
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A Strategic Approach to Data Quality
“To tackle today’s Data Quality challenges, you need a more strategic approach,” said Nigel Turner, Principal Consultant, Global Data Strategy.
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What Are The Benefits Of Cloud Data Warehousing And Why You Should Migrate
Since then the concept has evolved and taken on a life of its own. Increasing challenges and complexities of business have forced data warehousing to become a distinct discipline. Over the years this has led to best business practices, improved technologies, and hundreds of books being published on the topic.
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Harness the power of data literacy through democratizing data
Author Jordan Morrow weighs in on enterprise strategies to improve democratizing data through expanded use of BI and augmented analytics.
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The Future of the Data Engineer
Is the data engineer still the “worst seat at the table?” Thoughts on the past, present, and future of tooling, processes, and culture in our industry.
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Essential Responsibilities and Skills of a Data Engineer
Quite often, it is observed that people, as well as organizations, are ignoring essential skills for a Data Engineer. In this detailed article, I will cover all the essential skills to become a Data Engineer.
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10 Data Literacy Skills to Become a Data Citizen
Data literacy skills are increasingly top-of-mind for corporate learning and development initiatives. A recent webinar guest, Daryl D’Cruz, shared, “data literacy skills are the building blocks of digital transformation.”
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Opportunities and projects in the Data Engineering space.
In the end, advancing your career is all about getting the right opportunities at the right time and a
good portion of luck.
These are some interesting things going on in the Data Engineering space and you
probably don't want to miss them.
Python Project for Data Engineering
This mini-course is intended to apply foundational Python skills by implementing different techniques to collect and work with data. Assume the role of a Data Engineer and extract data from multiple file formats, transform it into specific datatypes, and then load it into a single source for analysis.
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Data Engineering Project for Beginners - Batch edition
A real data engineering project usually involves multiple components. Setting up a data engineering project, while conforming to best practices can be extremely time-consuming.
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SQL Project for Data Analysis using Oracle Database-Part 3
In this SQL Project for Data Analysis, you will learn to efficiently write sub-queries and analyse data using various SQL functions and operators.
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Udacity Data Engineering Projects
Few projects related to Data Engineering including Data Modeling, Infrastructure setup on cloud, Data Warehousing and Data Lake development.
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DEDS - Data Engineering for Data Science
The European Joint Doctorate in "Data Engineering for Data Science" (DEDS) is designed to develop education, research, and innovation at the intersection of Data Science and Data Engineering
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Apache Spark
Spark is a fast and general cluster computing system for Big Data. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Spark Streaming for stream processing.
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DataSF
Search hundreds of datasets from the City and County of San Francisco. Or browse on the data catalog
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Netflix Data Engineering
This repo is created to content the presentation, code and data for the Data Engineering WiBD Workshops at NFLX.
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