As humans become increasingly dependent on technology, it’s clear that electronic devices are the future. As a result, more and more people are looking for jobs in this sector. Since the internet runs on data, it’s natural to stumble upon data engineering and wonder if data engineering can be a good career.
Data engineering is a good career choice as it is in high demand and pays well. Data engineers rank among the top emerging jobs on LinkedIn, and the need for them will only skyrocket as technology progresses. The job also allows you to make a significant impact on the world at large.
This article will discuss the top reasons why data engineering is highly lucrative and an attractive career choice for tech enthusiasts. We will also look at some of the things you should know about the field and how you can become a data engineer.
Important Sidenote: We interviewed numerous data science professionals (data scientists, hiring managers, recruiters – you name it) and identified 6 proven steps to follow for becoming a data scientist. Read my article: ‘6 Proven Steps To Becoming a Data Scientist [Complete Guide] for in-depth findings and recommendations! – This is perhaps the most comprehensive article on the subject you will find on the internet!
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Why Data Engineering Is an Excellent Career?
Data science has become somewhat of a buzzword these days. An increasing number of people are looking at data scientists, data engineers, and data analysts as career options. All of these fields make for promising careers because they form an essential part of online business strategy.
So, to answer the question: yes, data engineering is undoubtedly one of the best jobs in the tech industry. However, before you begin studying data engineering, it’s crucial to understand its importance in the broader industry and its pros and cons. Here are the top four reasons why data engineering is an attractive career choice:
Data Engineering Is In High Demand
Data engineering was reported as the fastest-growing job in technology in 2019 in the Dice 2020 Tech Job Report. The number of open data engineer positions grew by 50% in a single year. It is safe to say that the demand for data engineers has exceeded the supply.
This is because companies now realize that data engineers are the key to unlocking the true potential of their data. Be it an established organization or a new startup. Every company is looking for capable data engineers to help grow their business. Data engineer jobs are at the top, along with data scientists and machine learning engineers.
A Career In Data Engineering Is Future-Proof
Technology is the future. Our dependence and advancements in technology will only keep growing. The demand for data engineers will increase in the same proportion. Data engineering will always stay relevant and never go out of fashion. The Dice 2020 Tech Job Report projects that the demand for data science jobs will increase by 38% in the next ten years.
Since businesses run on data, companies need educated people to process it and arrive at practical conclusions. Data collection and storage are the foundation of any data strategy. Only then can we optimize the data for machine learning.
This means data engineers are the backbone of data science. Their efficiency directly impacts the effectiveness of the entire data strategy. They are the backroom people on whose shoulders data scientists and data analysts stand.
Data Engineering Pays Well
Data engineering is highly lucrative. It ranks among the top-paying tech jobs in the market. According to salary.com, the average data engineer salary in the US is $107k. Indeed.com reports an even higher pay, showing an average base pay of $132k. Lastly, StackOverflow Developer Survey 2020 reveals that data engineers make an average of $125k a year.
Whichever data source you take, it’s evident that data engineers take a decent amount of money home every year. But why are data engineers being paid so much? Data engineering skills like SQL, Shell, and Python regularly rank among the highest-paying skills in StackOverflow’s developer surveys.
Data Engineering Presents Excellent Growth Opportunities
There are many career paths you can take once you’ve entered the industry as a data engineer:
- First of all, you can stay in the same job and become a senior data engineer, handling more complex data pipelines and leading a team.
- You can easily transition into software engineering since you’ll already be familiar with ETL and data layers.
- Data analytics is another option. Data engineers serve the backend of the apps used in analytics, which means they’re already familiar with the technologies.
- Lastly, you can also become a project manager. You’ll have an eye on what precisely the other data engineers, data analysts, data scientists, and clients are doing.
What You Should Know Before Pursuing Data Engineering?
We’ve seen how data engineering is one of the best career options in the tech industry. However, there are some things you should consider before you start learning programming languages for data engineering. These are not drawbacks per se, but just something you should remember about the job role.
Data engineers, as the name suggests, involves working with data all the time. You need to have strong developer skills for this position. A programming background can make you stand out. However, it doesn’t mean degrees and certificates are everything. Showcasing the projects you’ve worked on also goes a long way in landing that dream job.
Data Engineering Demands a Lot of Technical Knowledge
Data engineers work hard behind the doors to work out the data for internal customers, i.e., data analytics and data scientists. They make sure that the data is correctly gathered and processed so that other professionals can then interpret it and apply machine learning/AI to it. Data engineers also control the cost of securely saving and transferring the data as required.
The essential skills required for becoming a data engineer are Python, R, and SQL. However, they also need to know several more technologies to choose the right tool for any particular job.
Experience Is More Important Than Education In Data Engineering
I just said that apart from the major programming languages, data engineers need to know several more technologies and stay up-to-date with them. And this comes with experience. Although education has its place—and certain certifications help you land your first job—hands-on experience has much more value.
If you ask a typical data engineer, they’ll tell you that most of the skills they possess have been picked up on the job. So don’t fuss over your background. If you’re passionate and motivated, you can certainly make a name for yourself in the industry.
Data Engineering May or May Not Match Your Personality
This doesn’t just apply to data engineering; it goes without saying for any career. Data engineering is a lucrative job, and it pays decently. But you also need to consider whether you’re really built for that kind of thing.
Most of your day will be spent looking at a computer screen filled with numbers. Maybe you’ll have occasional meetings, but your job’s central aspect requires you to work alone. These long stretches of solitude may prove to be soul-sapping for people who like human interaction. On the other hand, introverts probably won’t face this problem.
Author’s Recommendations: Top Data Science Resources To Consider
Before concluding this article, I wanted to share few top data science resources that I have personally vetted for you. I am confident that you can greatly benefit in your data science journey by considering one or more of these resources.
- DataCamp: If you are a beginner focused towards building the foundational skills in data science, there is no better platform than DataCamp. Under one membership umbrella, DataCamp gives you access to 335+ data science courses. There is absolutely no other platform that comes anywhere close to this. Hence, if building foundational data science skills is your goal: Click Here to Sign Up For DataCamp Today!
- IBM Data Science Professional Certificate: If you are looking for a data science credential that has strong industry recognition but does not involve too heavy of an effort: Click Here To Enroll Into The IBM Data Science Professional Certificate Program Today! (To learn more: Check out my full review of this certificate program here)
- MITx MicroMasters Program in Data Science: If you are at a more advanced stage in your data science journey and looking to take your skills to the next level, there is no Non-Degree program better than MIT MicroMasters. Click Here To Enroll Into The MIT MicroMasters Program Today! (To learn more: Check out my full review of the MIT MicroMasters program here)
- Roadmap To Becoming a Data Scientist: If you have decided to become a data science professional but not fully sure how to get started: read my article – 6 Proven Ways To Becoming a Data Scientist. In this article, I share my findings from interviewing 100+ data science professionals at top companies (including – Google, Meta, Amazon, etc.) and give you a full roadmap to becoming a data scientist.
Conclusion
Data engineering is an attractive career choice for many young tech enthusiasts. Because this position pays well over $100k annually. Data engineering is also a recession-proof and future-proof field since the world will always need people who collect and store data. You can work your way up in the same job or switch to another similar position easily.
Plenty of information is available on the internet about how to become a data engineer. After reading this article, if you feel like this job is for you, I highly recommend this for you and start learning as soon as possible!
BEFORE YOU GO: Don’t forget to check out my latest article – 6 Proven Steps To Becoming a Data Scientist [Complete Guide]. We interviewed numerous data science professionals (data scientists, hiring managers, recruiters – you name it) and created this comprehensive guide to help you land that perfect data science job.
Affiliate Disclosure: We participate in several affiliate programs and may be compensated if you make a purchase using our referral link, at no additional cost to you. You can, however, trust the integrity of our recommendation. Affiliate programs exist even for products that we are not recommending. We only choose to recommend you the products that we actually believe in.
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