In the world of data science, data engineering as a job profile is gaining a lot of attention. According to the DICE Tech Job Report, data engineering has experienced the largest growth over the last two years among tech-related professions.
The demand for data engineers is skyrocketing. As reported by AIMResearch that the data engineering market will grow at a CAGR of 36.7% in the next five years, growing from USD 18.2 billion in 2022 to USD 86.9 billion in 2027.
If you find data fascinating and are interested in a career in the technology sector, a data engineer can be the ideal career choice for you. Data engineering is an in-demand future profession that will surely keep you on your toes.
This article is crafted to help you to get started with an endeavoring journey on “how to become a data engineer”, best job roles in data engineering, data engineering certification, etc.
First things first, let's get a sound understanding of “what is big data engineer”, is before we dive into knowing “how to become a big data engineer?”
So, Let’s get started!
Data engineering is the process of creating and constructing systems that enable users to gather and evaluate unprocessed data from many sources and formats. These technologies enable users to discover useful data applications that firms may employ to succeed.
Understanding what data engineering is all about understanding the "engineering" component.
According to the U.S. Bureau of Labor Statistics (BLS), “Big data is the gathering and analysis of information that businesses are producing at previously unheard-of scales. A large portion of the data originates from relatively recent technology like social networking, smartphones, and e-commerce.”
Big Data is processed to extract valuable information, which enhances overall performance. Organizations can improve the quality of their products, business choices, and marketing by doing this. And experts in the field of big data help with this task.
The position of a big data engineer is among the top in this industry and going through the data science courses can prepare you for the industry. Professionals that create, maintain, test, and assess a company's big data infrastructure are known as big data engineers. They have fun with big data and put it to use for the development of the company.
Data engineers create systems that gather, handle and transform unprocessed data into information that data scientists and business analysts may use to evaluate it in a number of contexts. The ultimate objective of a data engineer is to open up data so that businesses can utilize it to assess and improve their performance.
Following are some typical tasks a data engineer does –
Working for smaller businesses frequently entails performing a wider range of data-related duties in a generalist manner. The management of data warehouses, including the loading of warehouses with data and the development of table schemas to monitor where data is kept, is the responsibility of certain larger firms' data engineers.
In the coming sections, we will discuss in-depth on how to become data engineer, but before that let’s go through the top reasons why data engineering fascinates so many aspirants.
From excellent growth opportunities to earning potential to future scope, there are so many reasons why people search for how to become data engineer. Here we have listed a few reasons why you should choose a career in the data engineering roadmap–
1. Greater Employment Opportunities for Big Data Experts
Big Data is unquestionably becoming a buzzword and a growing demand for enterprises in the next years as a result of the advancement of technology.
Big Data specialists are in high demand across enterprises today. Candidates with knowledge and experience in big data are highly sought after. By 2020, there will be 2,720,000 more employment in US data experts, according to IBM.
2. Salary Increase
The salaries of qualified experts are being impacted by the high demand for Big Data specialists. According to Glassdoor, the following are the salaries offered by various companies based on the individuals who work in these companies in the US region:
Big Data experts' pay is strongly correlated with things including their degree, work experience, topic expertise, and technical understanding. A solid understanding of tools and technologies is also required, as well as the ability to comprehend and resolve real-world Big Data problems.
3. Massive Adoption of Big Data
According to Forbes, the usage of big data in businesses climbed from 17% in 2015 to 59% in 2018, for a 36% compound annual growth rate (CAGR). The decision has resulted in Big Data being one of the top objectives of the participating businesses, according to Intel's "Peer Research – Big Data Analytics” survey. According to the poll, 45% of respondents believe that Big Data would provide greater business benefits in order to dominate the Big Data market.
Big iota Insight Out projected that the market for big data will increase from its present size of $40 billion to $80 billion, generating $187 billion in revenue.
4. Various Options in Job Titles and Responsibilities
Depending on the abilities they have already acquired, big data professionals have access to a variety of job titles. Aspirants for Big Data jobs have a wide range of possibilities, and they are free to align their career trajectories according to their professional inclinations. The following are some of the jobs that big data specialists may hold:
5. Use in Different Businesses and Industries
Today, practically every company uses big data. Professional, Scientific and Technical Services (27%) is the top sector for hiring big data specialists, followed by Information Technology (19%), Manufacturing (15%), Finance and Insurance (9%), and Retail Trade.
Hopefully, you get enough idea on why people see data engineering as a great career options. Next, we will move to the main topic – how to become data engineer.
You can begin your data science career path with the right skill set and knowledge. A bachelor's degree in computer science or a closely related subject is the first step toward how to become a data engineer. Acquiring a degree will lay the groundwork for the information you'll need in this rapidly changing sector. To grow your career and open doors to opportunities with higher payouts, think about getting a master's degree. Follow the step-wise process on how to become a data engineer –
Step 1: Obtain a Degree
Even entry-level data engineers require a degree of some sort, mainly in computer science, software engineering, physics, or applied math when it comes to how to become a data engineer. In a perfect world, this would also help you acquire the “soft” skills necessary to succeed in the position, in addition to giving you a strong foundation in the fundamentals of software development and/or data.
Step 2: Enroll in Recognized Data Engineering Certification
Maybe you've achieved success in a different industry or have a degree already. If so, taking a recognized online course in a subject like data analytics is another choice. Compared to a full degree, a data engineer certification course is a reasonably cost-effective approach of ‘topping up’ your relevant skill set. You can concentrate on important topics like big data architecture, machine learning, or data analytics, depending on the course you choose. In a thorough and well-designed data engineering certification course by JanBask Training, you will be trained in the latest industry trends and enhance your ability to become a data engineer.
Step 3: Gain Practical Experience
Data engineering isn't exactly a “first job out of college” type of career, even with a certificate. This is progressively beginning to change as data engineering develops into a specialized discipline. The majority of entry-level data engineering positions require experience, but the definition of “experience” is frequently quite broad, which is advantageous. It's possible that you've previously worked in a data-related position (perhaps as an analyst or in data science), in software development, or as an intern in a related field. Keep your options open when looking on how to become data engineer.
Step 4: Learn about Your Databases
Make sure your broad understanding of databases and the tools you could use to administer them are up-to-date. It is another basic step on how to become a data engineer. Because they serve as the foundation for bigger infrastructures, databases are an essential component of data engineering.
Step 5: Develop Your Knowledge on Tool Sets
Your work prospects will be much enhanced by expanding your knowledge and skills using various web-based data engineering tools. There are many options available, but a couple to take into account are the cloud architecture from Amazon Web Services, the Apache Cloud stack, and Microsoft's SQL Server Management Studio. Even while you don't have to become an expert in every one of these tools when moving on the path how to become a data engineer, it's still vital that you at least have a fundamental understanding of them.
Step 6: Embrace Work Opportunities
The route to big data engineering is a little tough. Don't give up if your ideal position isn't found immediately. Big data engineering is better viewed as a long-term goal, particularly if you lack experience. Although they may not be directly tied to data, many related careers have steep learning curve.
A great first step toward data engineering is becoming a data analyst. Any position that involves computers or data will help you develop valuable abilities. In the end, data engineers with a breadth of experience gained from a diverse range of positions at various levels are the most productive.
So, this is how to become a data engineer. Follow this process step-by-step to land your dream career.
Data engineering job pays well, it is the main benefit of choosing this as a professional career. That's Why the number of searches on how to become a data engineer is increasing rapidly.
The average income for a data engineer or data engineer salary ranges from $65,000 to $135,000, depending on your school background, professional certifications, number of years of experience in the area, other abilities, etc. The Bureau of Labor Statistics reported the following top positions' yearly salaries for the year 2019:
According to Glassdoor, the basic pay for data engineers was projected to be $102,864 per year in 2020.
According to Indeed.com estimates, Data Engineers can make up to $129,415 per year plus a $5,000 incentive that may be offered. The average Data Engineer pay in the US as of April 2021 ranges from $90,000 to $126,133. This is one of the highest-paid skills in the business, and it is clear from these reports that this trend will continue—or, should we say, develop and grow—in the near future.
Data engineering is a wonderful career option for aspirant data professionals as it is one of the most in-demand jobs in the data science industry.
If you are someone looking for a shooting career in data engineering then you are in the right place.
We strongly advise you to pursue the Data Engineering Certification Course if you are committed to working in the field of data engineering but are unsure of where to begin or how to become a big data engineer. This track will provide you with the theoretical and practical expertise you need to excel in this field.
Learning the required skill sets and practicing them well, working on gaining real-time industry exposure will open up doors for a rewarding and much-in-demand career as a Data Engineer.
Feel free to share your doubts and questions in the comment below, and our experts will be more than happy to guide you ahead!
Q1. What is big data engineering?
Ans: The process of planning, constructing, testing, and maintaining intricate data processing systems that deal with massive amounts of data is referred to as big data engineering.
Q2. What is a big data engineer? What does a big data engineer do?
Ans: A big data engineer is in charge of creating, maintaining, testing, analyzing, and assessing a company's data is known as a big data engineer. Large data sets are referred to as “big .”
Q3. How to become a big data engineer?
Ans: Big data engineers typically hold a master's degree, such as an online master's in business data analytics, in addition to at least a bachelor's degree. The extra years of education are essential for acquiring the numerous technical abilities required of a big data engineer.
Q4. How long does it take to become a data engineer?
Ans: The majority of data engineers land their first entry-level position after receiving their bachelor's degree, however it is also feasible to change careers from another data-related profession to become a data engineer.
Q5. Is big data engineering hard?
Ans: The job is incredibly challenging. It's a boring job, but it's extremely important. Like the unsung heroes of the data realm, data engineers. They have a really difficult profession that requires new technology and expertise.
Q6. Which degree is best to move the data engineer roadmap?
Ans: The minimum educational need for entry into this field is a bachelor's degree in computer science, software or computer engineering, applied math, physics, statistics, or a closely related discipline. It is the only thing required when it comes to how to become data engineer. For the majority of entry-level roles, you'll also need to have practical experience, such as internships.
Q7. How to become a data engineer?
Ans: Here is a process on how to become data engineer –
Q8. Is a Data Engineer a good career in 2023?
Ans: By 2023, the Big Data market will be valued at $77 billion. According to a poll, big data engineering job interviews will climb by 40% in 2020, whereas data science job interviews will only rise by 10%.
Q9. Who earns more data engineer or data analyst?
Ans: In general, data analysts earn $69,467 per year. You can make between $46,000 and $106,000 a year depending on your region, experience, and talents. On the other side, a data engineer makes on average $112,288 annually.
Q10. Do data engineers code?
Ans: For a job in data engineering, everyone is in agreement that you need good development abilities. You will need to write scripts and possibly some glue code, according to Ng. "Today, everything is code, including pipelines and infrastructure. Although courses are fine, practical experience is still superior.
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