Data Engineering deals with building systems to collect, store, analyze, and craft meaningful data. Its use-case spans over every industry wherever you find some form of data.
And data engineers are the backbone of such industries. Without making sense of the data available, organizations and analysts will remain clueless.
But, how do you become a data engineer? Is it a good career option for the present? Does it have the potential for the future?
In this article, I shall present answers to all of your questions along with some course recommendations to start your career as a data engineer, if you decide.
How Do You Become a Data Engineer?
A data engineer needs to develop several skills, which come with experience and certifications. To get a head start, you need to have mastery over coding languages like Java, R, Scala, Python, SQL, and NoSQL.
You will have to explore databases, data storage, automation/scripting, machine learning, data security, big data, and cloud computing. Of course, the requirements might vary as per the job role, but in other words, you must know a wide range of things to become a data engineer.
So, it is unlikely that you get to be a data engineer as soon as you start your career. You will have to start as a software engineer or analyst and then move up to a data engineering role.
Is Data Engineering a Promising Career?
Data is the most precious asset now, even when compared to natural resources like oil.
Companies invest trillions of dollars to build ways to collect, process, and store data. It is not just about your personal information, but everything in the world.
And it's growing at a rapid pace.
As the value and amount of data increase, the demand for data engineers will also increase.
As per a 2021 LinkedIn report, data engineering was one of the top jobs on the rise. And, it is expected to be one of the most trending sectors in the future as well.
If talking about its potential—as long as data exists, there will be requirements to build systems to process and make it useful. So, it definitely sounds impressive for a career choice.
How to Approach Data Engineering as a Career Path?
Data engineering can be a challenging career path. Where do you start? What exactly do you need to learn?
It is important to note that most data engineers learn on the job without even realizing it. You start as a Data Scientist or Analyst and hone your skills to take up a better position as a Data Engineer.
Let me mention some key highlights for the things you have to know to advance your career as a data engineer:
- Programming skills are a must: For starters, you need to know the basics of Python and R. These are the two most significant languages for the field. You can also explore more languages; you cannot ignore these two languages.
- Database knowledge: Considering that you will be dealing with raw data, you need to know SQL, how to optimize SQL queries, manage a database system (or RDMS—Relational Database Management System). The basics will give you a head start, but you need the knowledge to manage complex database systems for businesses.
- Data warehousing: While this is possible only when you are learning on the job, you will have to assist data engineers in managing unstructured data and assessing it for business decisions.
- Operating system knowledge: You should have a good command of using UNIX-based systems, Linux systems, Solaris, and Windows systems as well.
- Machine learning: At least, the basics of machine learning for data modeling and analysis should be of help.
- Big data tools: Considering you will be dealing with massive amounts of data, it is best to know some use-cases of big data tools like Apache Hadoop.
Note that these are not the exact prerequisites of the job role you want. We only list these to give you a head start and explore the basics/necessities to become a data engineer.
You may need to learn more about other tools or programming languages as you progress in your career path.
In addition to some of the above information, here are some course recommendations to make it easy for you to learn what's required to become a data engineer:
Data Engineering Essentials Hands-on (Udemy)
Udemy features valuable learning resources for just about anything, and data engineering is no exception. The Data Engineering Essentials is a highly rated paid course that gives you insights on using key languages like SQL, Python, and Spark.
It focuses on several hands-on tasks and exercises as well.
The course lets you set up a development environment to learn to build data engineering applications using the Google Cloud Platform. You learn the essentials and some relevant abilities to practice numerous things.
If you do not prefer reading the whole time but want to focus on hands-on practice, this course should serve you well.
Data Engineering Basics for Everyone (edX)
If you want to explore the basic concepts and everything associated with data engineering, this course should be a perfect fit. Data Engineering Basics for Everyone deals with the necessary fundamental concepts; a beginner needs to proceed further. You will not find any hands-on exercises or advanced explanations, but it's just about fundamentals.
IBM offers this course through edX, a reputed online platform with credible certifications and quality courses. It is a free course that includes an optional premium if you need the certificate.
If you want a head start to figure out the basics of data engineering, you might want to try this course. You should get a good idea of the depth of the field and if it is interesting to continue.
Data Engineer Nanodegree (Udacity)
A Nanodegree program by Udacity gives you more advanced insights into a subject. Compared to some fundamental courses, you will need some knowledge to pursue a nano degree.
With a “Become a Data Engineer” nano degree, you should be able to step up from an entry-level data engineer role to a better production-ready technical candidate. The program will also revisit some basic concepts, but you need to check the course's prerequisites.
Note that the nano degree program costs significantly more than any other individual course. So, you might want to check its credibility, and if you require it, before purchasing it.
Data Engineering for Everyone (Datacamp)
Data Engineering for Everyone is a free course that does not involve any coding. It provides you with information about its fundamentals and what type of work is involved in data engineering.
You will be introduced to the responsibilities you are supposed to carry out after gaining the required skills in the data engineering field.
Datacamp's course is an exciting way to learn while gaining points/XP after completing the chapters. You can also opt for its paid courses with hands-on coding sessions and get access to various projects to expand your skills.
Modern Big Data Analysis with SQL Specialization (Coursera)
The Big Data analysis course is offered by Cloudera on Coursera. You can audit the content for free. But if you want certifications, quizzes, and access to all the resources, you will need the Coursera subscription, or you may ask for financial aid.
If you are looking to focus on specific work in the field of data engineering, this should be a great start. You do not need any prior experience to take this course.
But you should be able to get a good command of Big Data and SQL for data analysis after taking this course. Even if you have some experience, this course should polish the necessary skills for working with large-scale data using SQL.
Data Engineering Foundations Specialization (Coursera)
Another exciting course on Coursera focuses on giving you insights on the fundamentals while also helping you gain hands-on experience with coding and relational database.
If you are not happy with the free courses available to polish your fundamentals about data engineering, IBM's Data Engineering Foundations specialization should serve you well.
It also features hands-on practice exercises that aren't overwhelming but should come in handy.
Introduction to Data Engineering
The Introduction to Data Engineering course should be a good start, whether you are learning it for the first time or brushing up on your fundamental knowledge.
Once you master the fundamentals, you do not need help figuring out the resources necessary to know advanced stuff. So, you will find various introductory courses featured in this list.
Become a Data Engineer (LinkedIn)
A learning path that you can find in the LinkedIn learning portal. It is a collection of different courses that helps you learn data engineering concepts. You get to know the foundations, an overview of NoSQL, Big Data, real-time application, SQL tips, and more with the “Become a Data Engineer” learning path.
You can opt for a LinkedIn premium 1-month trial to access the resources and learn from them. If you have already used up the trial, you will need to reactive LinkedIn premium to access these courses.
LinkedIn Learning provides high-quality resources fit for beginners and professionals. It can also be a convenient way to quickly add your certifications/skills to your LinkedIn profile.
Learn New Concepts to Advance Your Career
With several online courses, and the platforms available, it is easier than ever to learn new concepts without making a big effort. While every course offers something different, it should help you get started in your journey of becoming a data engineer.
You can start with the free courses and then move to the paid options to polish your skills and explore more about the subject. The courses which offer hands-on exercises should help you gear up for the work you intend to do in your job role.
Data engineering is an industry with constant growth and opportunities. You might want to explore it as soon as possible.
Here are some of the best Data Analytics Courses.
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