How to Become a Data Engineer in 2021?

How to Become a Data Scientist in 2021

Welcome to another data science Article in this article, we’ll explore one of the top careers in data science. This might surprise some of you, but this time, we’ll talk about becoming a data engineer. In this Article, you’ll discover who the data engineer is,what they do, how much they make, and what education and skills you need to become one.

Let’s talk about the data engineer and everything you need to know about that career path. Data engineers just one of the most coveted data science job roles out there. So keep in mind the other options is 

  • Data analyst
  • Bi analyst
  • Data architect
  • Data engineer
  • Data scientist

So who’s the data engineer, and more importantly, what sets them apart from everybody else?

Who is Data engineers?

Data engineers are the Jedi Knights of data science. They rely on a blend of analysis, wisdom, experience and judgment to make key decisions for company success. A data engineer is a self starter, who is inspired to complete more than your usual number of tasks. What does that mean?

Data engineers are the ones who take things further up the data science pipeline. They use the data architects work as a stepping stone and then pre processes the available data. These are the people who ensure the data is clean and organized and ready for the analysts to take over.

Data engineers also implement complex large scale Big Data projects with a focus on collecting, managing, analyzing and visualizing large datasets and all that massive amount of overwhelming raw data.

Well, they are the ones turning it into insights using various tool sets, techniques and cloud based platforms. You might think that’s enough work for one day, not for the data engineer. Data engineers are also responsible for building and maintaining ETL pipelines, which make crucial data accessible for the entire company.

And when they get a minute, they lend a helping hand to bi analysts by designing and supporting bi platforms, who makes sure all big data applications are available and performing properly. Again, data engineers and to top it all off.

They are great team players, a data engineer and knows how to actively collaborate with data scientists and executives to build solutions and platforms that meet or even exceed a company’s business needs. So how does all this responsibility translate into the data engineer salary?

Data engineer salary?

We ask glassdoor and payscale to give you a good answer. In the US, the average pay for a data engineer who’s just getting started in his career is $103,000. Of course, once you hit the four to six years experience mark, you can expect your compensation to rise to $117,000. Plus, you’ll be eligible for additional bonuses in the region of $10,000.

Looking for a data engineer job in the UK, according to PayScale research, even if you have less than one year experience, you get an average pay of 30,000 pounds. This includes bonuses and overtime pay naturally with experience comes a higher salary

A data engineer with one to four years of experience earns an average total compensation of 41,000 pounds. And it only gets better. Once you have five to nine years of experience, your annual pay can hit 54,000 pounds, big data, big rewards. But what does it take to become a data engineer?

Data engineer path.

The data engineer path is one of the best choices you can make if you’re driven to succeed in data science. But what if you’re new to the field and you’re not sure you’ve got what it takes to get there? Don’t worry.

Here are the steps that will lead you to a data engineer career. Let’s consider education. First, what academic background Do you need to become a data engineer?

1. Academic background

Obviously, a degree in software engineering, computer science or information technology will give you a flying start. However, if that’s not the case, you can still make the cut. But you still need skills in computer programming and software design statistical modeling and regression analysis, Python SQL and machine learning.

Now, before you rush into writing off your dream job, you should know that acquiring these skills is absolutely possible even for complete beginners. Today, there are plenty of qualification programs and online certificate data science trainings.

Once you complete the courses and gain experience with real world exercises and projects, you will have the skills confidence and the portfolio to apply for a data engineer position.

Next, let’s talk about skills and qualifications. What do you need in this department to become a data engineer?

2. Skills and qualifications.

Well, as we mentioned, a data engineer job comes with certain many responsibilities. So here’s a list of competencies and skills you need to become a data engineer who knows their stuff and technical skills for a data engineer.

Knowledge of data modeling for both data warehousing and big data is a must Along with experience in the Big Data space Hadoop stack like Mr. HDFS, pig hive, etc. Of course the ability to write, analyze and debug SQL queries will help you score high on any employers recruitment list.

One more hand, make sure you gain some experience with at least one scripting language, for example, Python. And don’t forget the basics. Mathematics is never out of style in the data science competitive universe.

  • Practical skills

How about practical skills? Nothing unusual if you ask us that is of course, considering you have the Jedi powers of data engineers. “So Young padawans” focus on these who should if to succeed as data engineers, you want to hone your data visualization skills make Tableau or Power BI your best friend,

  • Analytical skills

Ability to make sound decisions, even in the absence of good complete information, you must make sure you follow through on commitments and make sure others do the same

  • Personal responsibility And communication skills

personal responsibility for decisions actions and failures, establishment of clear processes for monitoring work and measuring results. Design of feedback loops into work, strong attention to detail, the ability to think critically and conceptually,

but it’s not all about what you know, soft skills are just as important. So you’ll need to develop very strong communication skills in a variety of communication settings.

That means more than a meet and greet in one on one meetings, and small and large groups gatherings among diverse styles and position levels.

Okay, now you know what it’s like to be a data engineer and how to get there. However, better preparation means higher chances of success. So if you feel like you still need additional career advice and a more detailed analysis of the career opportunities in data science.

Then don’t forget to Comment your question in comment box share it with your friends,

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