Here’s How You Can Become A Data Engineer

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Professionals in the discipline of data engineering construct, develop, gather, store, certified business analytics professional, and analyze data. It is a vast field, and many think of it as a fusion of data science and software engineering.

What Does A Data Engineer Do?

We’ll use a plumbing analogy to help you comprehend. Similar to how a plumber moves a water pipeline from the plant to the kitchen sink, a data engineer’s job is shifting data from pipeline A to pipeline B. A data engineer also keeps up the current data infrastructure so that it can easily transform unprocessed data into usable data. To guarantee that water runs freely when you take a bath, plumbers maintain pipelines like this.

A data engineer extracts save and formats raw data into a format that may be used. To assist in making data-driven decisions, they collaborate with other data professionals like data scientists, business analysts, and machine learning engineers.

A data engineer must be technically skilled in a variety of programming languages and technologies, including machine learning, MySQL, Spark, Python, AWS, distributed systems, data architecture, and others, to do all of the aforementioned tasks.

What Does It Take to Become A Data Engineer?

When it comes to your journey to becoming a data engineer, the proverb that “a trip of a thousand miles begins with a single step” is certainly true. It will be beneficial if you begin by learning how you plan to get there. You may start by taking stock.

1. Create A Career Strategy

Many college students choose to major in computer science because data engineering is a field that combines software engineering and data science. Additionally, many firms favor applicants with at least a bachelor’s degree in computer science or a closely related subject, such as data science. To become a data engineer, you don’t need a degree; a boot camp, a certification, or a self-study course can all be acceptable.

Depending on the educational route you choose and the learning curve that goes along with it, you can estimate how long it will take you to become a fully-fledged data engineer. Below, we’ll go over several choices with you.

2. Complete Education

Your education can be finished in as little as 10 weeks.

3. Acquire Practical Experience

Employers are constantly looking for data engineers who can back up their knowledge with a strong portfolio. Thinking creatively and acquiring experience is crucial in this regard. Fortunately, there are a few different methods you can do it.

  • Intern For A Company

Work on open-source initiatives and compile a portfolio of your program in business analytics Take part in hackathons for data engineering. Typically, internship and hackathon resources are offered by colleges and boot camps, but if you want to be more proactive in your research, you might want to look into the following sources:

  • Participate in open-source initiatives
  • Getting ready for interviews in data engineering
  • Regularly updating your online portfolio is important because it will help you in your job search.
  • Estimated time: You may commit anywhere between three and six months over the phase.

4. Obtain A Certification (optional)

Obtaining a certification will make you appear more credible to some employers. It makes sense to hold off on getting certain certifications until later in your career because some of them need you to have a lot of expertise in your profession.

Several appropriate certifications for data engineering include:

  • Microsoft Certified Data Engineer
  • AWS certificates from Amazon
  • Intelligent analytics and data engineering
  • Estimated time: Some certificates may demand a certain amount of experience as a prerequisite, while others may not. You’ll also need to set aside money for exam costs.

5. Get Ready To Conduct A Job Search

It can be intimidating to get ready for a job search program in business analytics. However, you will benefit yourself if you are well-prepared. Consider performing the following before even applying for positions in data engineering:

Create A Strong Portfolio: Volunteer to work on worthwhile projects, and at all costs, avoid duplicating work. You can navigate how to use code repositories and learn how to build a portfolio using GitHub.

Getting Ready For Interviews: Get technical in data engineering tools like SQL, practice problem-solving, and practice soft skills by becoming an expert in behavioral interviewing as you get ready for data engineering interviews.

Using professional networking and meetup groups like LinkedIn, connect with alumni and networks.

Estimated duration: This stage might last for months.

6. Look For Employment In Data Engineering

You are now prepared to start your job hunt, congrats! Utilize the many employment boards available, including LinkedIn, Indeed, Handshake, etc., to apply for pertinent positions.

Don’t forget to use a spreadsheet or any comparable program to keep track of your applications.

Estimated Time: This stage is the hardest and most subjective. The frequency of your applications and responses from employers will be entirely dependent. A data engineering job search could take 3 to 8 months. You will also encounter rejection, but don’t let it stop you.

How Much Time Does It Take To Train as a Data Engineer?

Depending on the path you choose, it could take three months or six years. If you want to pursue a bachelor’s degree, it will take you four years. Many data engineers make the switch from other data-related positions like data analysts to data engineering, even if the majority do land their initial entry-level jobs immediately out of college. Two prerequisites are fundamental:


As we previously said, you must know about data engineering to work in the industry. Although it is not necessary, companies frequently prefer candidates with a bachelor’s degree in computer science or a closely related field. However, this does not imply that you cannot work as a data engineer without a college degree. To help you reach this objective, we have provided thorough instructions on the various skill paths above.

Soft Abilities

To succeed in a data engineering profession, you will require more than just technical expertise. You will contribute to your firm as a multidisciplinary professional while also moving up the career ladder. Important soft talents include:

  • Strong communication abilities
  • Exemplary work ethic
  • Critically analyzing
  • Adaptability
  • Collaborative effort

Wrapping Up

Data engineers are essential to managing both the data produced by our digital activities, and are certified business analytics professional. They create, test, and manage the architecture for data storage, including databases and massive data processing systems. A big data engineer creates continuous pipelines that go to and from enormous pools of filtered data so that data scientists can draw pertinent data sets for their analysis, much like creating a physical structure.