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Tips to Become a Data Engineer

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  • Difficulty Level : Hard
  • Last Updated : 15 Oct, 2021
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Data Engineering is one of the most coveted careers options today and a highly lucrative one at that. And if you are wondering what data engineering entails, what will be the growth trajectory, or how to become a data engineer, you have stumbled upon the right article. We will try to answer all these in this article.


Data Engineers basically construct reservoirs to store data and also manage these reservoirs. They are basically guardians of the data which is available to companies. They take care of all our personal information and preserve it. Data engineers help make loads of unorganized data into usable data so that business analysts and data scientists can interpret it.  

A data engineer arranges datasets according to industry needs. They test, build, and maintain the main database architecture. They are also responsible for developing algorithms to convert data into useful models and create new data analysis tools. Data engineers collaborate with management teams to know the company’s objective.

Data Engineering Jobs

Before diving into the how-to part, let’s first have a look at some of the popular industries and companies that hire data engineers.

Some of the common industries that hire data engineers are:

  • Healthcare
  • Telecommunications
  • Banking, Financial Services, and insurance
  • Automotive
  • Media and Entertainment
  • Cyber Security
  • Information Technology

Some Popular companies that are hiring data engineers:

  • Amazon
  • Walmart
  • JP Morgan Chase
  • Accenture
  • IBM
  • Apple
  • Microsoft
  • General Motors
  • Samsung
  • Hyundai

Now, here are the most effective tips for becoming a Data Engineer:

1. Learn the Required Skills

A. Develop the skills needed for Data Engineering

Skill is the key. It opens doors to many new opportunities. Skills are required for every job and one needs to learn the skill set required so that they have an outline of what the job entails. Following are the skills you require to be a successful data engineer:

  1. Master the databases: As a data engineer you will primarily be required to work with databases, creating, managing, and extracting data from databases. There are two types of Databases (DBMS) that you will work with – (i) Relational databases (RDBMS) that use tabular form including rows and columns to represent a set of data. The programming language that is widely used for RDBMS is SQL. (ii) A non-relational database, on the other hand, does not use a tabular form to represent the dataset. NoSQL is usually the language that most data engineers are a master of.
  2. Learn the programming languages: Coding is a vital skill you require to work with data on a larger scale. Python is one of the coveted languages to master data science. Besides Python, you can also learn Java, Scala, etc. These help with analysis.
  3. Learn to handle the data with ETL (extract, transform and load) systems: The ETL process includes moving data from different sources of data to a single database. These tools help transform data into useful data.
  4. Learn to store the data: All the data can’t be stored in the same form. When it comes to large data you have to arrange it in different forms. This is similar to storing and arranging goods in a warehouse.
  5. Learn to store data online with Cloud computing: Knowing how to store data is great but you should also know how to store data online. Cloud computing deals with storing the data online to increase its accessibility.
  6. Learn Machine learning algorithms: Having a basic knowledge of machine learning comes in handy. Machine learning is not directly connected to data engineers but helps them get a better idea about a data scientist’s needs.
  7. Hone your communications skills: Like every other profession, data engineers are required to constantly interact with multiple people from data scientists, business analysts to fellow data engineers.

These skills will give your career a good start and you will have a better idea of how to become a data engineer and what being one is all about.  

B. Build Credibility with Certificates 

A certificate works as a validation of your skills. It gives an idea of your skills and experience to the hiring company. You can go for certified courses from various trusted platforms. You can also opt for core degree courses from universities. There is a popular certification by Google Cloud. Its cost is around 200 dollars. The certificate will be given on the basis of the score you gain in a 2 hours online/offline exam. The minimum required experience is 3+ years. Certificates will highlight your CV against tons of other candidates.  

2. Put Your Skills to Use

It is important to put to use whatever skills and knowledge one have gained. Practical application of these skills gives a rough idea about how much improvement one needs. It also helps clear basic concepts and solidifies these concepts. You can follow the below-mentioned suggestions to start with.

A. Build a Solid Portfolio  

How and where to build a portfolio?

Having a portfolio backs up the theoretical knowledge and certificates you have learned. It also shoots up the chances of landing a job against a pool of candidates. GitHub is a popular platform that many engineers use to compile their projects. Start by identifying the type of project you want to build, try to use a wider range of skills to showcase your expertise in various languages. It is always safer to include different types of projects since it will cater to various recruiters. showcase your skills and clear thinking through these projects.

A portfolio is used by companies to know about your passion related to a particular field. You can also add your projects to your LinkedIn profile to increase their value. Brush up your skills with projects. Learn new skills and acquire knowledge. Add these skills to your CV. These are the baby steps to start your journey to be a successful data engineer. Getting involved in industry projects will help you to brush your skills in your college days. You can add extra webinars or seminars that you have attended or organized in your portfolio. This step will help you get an idea about what a data engineer does and what your role will be.  

B. Start Working with Organizations as an Intern or as a Freelancer

You can contact different organizations using your Linkedin profile or do freelancing. Request them to give you some work, express your desire to work with the company and team, and share your profile with them. Working on entry-level projects in your college will give a boost to your career and confidence. Be an extrovert. Make connections with people. Learn something new every day. Having an internship will help you in your early career. An internship teaches you many things about the professional world and how the industries work. You can apply for these internships by directly going to the company’s website. You can also mail them if you are eager to learn.  

C. Crack an Interview

After learning all the required skills, now it’s time to upgrade yourself for the industries. Start applying for data engineering jobs on different job portals or look into the recruitment drives of companies. Before every interview brush up on your skills to crack the interview. Don’t forget to go through reasoning, verbal, and analytical skills. You can learn these skills through online platforms. Try to give mock interviews to prepare yourself for the final interview.  

3. Keep Learning

Once you land a job, you will realize that data engineering is an evolving career. However, you should remember that your learning does not stop here. It is important to constantly learn and grow while working with data. Languages change all the time and to keep growing as a data engineer you will need to follow these developments closely. Become a part of a community or create one that specializes in data engineering and related skills, this way everyone in the community can bring their insights and keep honing their skills.

Why should you consider data engineering as a career option?

Everything and everyone is going digital, every business be it small or large depends on data, without at times realizing that what they are using is data. Imagine a large cosmetics company running a survey to know whether their customers have seen any changes after using the company’s products, or just a review survey. Now the responses collected are in highly unorganized form using which one probably can’t draw conclusions. This is where a data engineer steps in. The data engineer will use algorithms to transform this raw dataset into a more useful dataset, which can be analyzed by the business analysts to draw conclusions.  

And it’s not just cosmetics companies, companies of all sizes and different industries rely heavily on data to draw conclusions, formulate product and marketing strategies, analyze customer behavior, etc. And where there is data, there has to be a data engineer! Still not convinced? Going forward, the use of data is only going to increase. Data engineering was also one of the top trending jobs in 2019, according to LinkedIn. Along with the high demand in the market, data engineering is a job that offers both growth and challenges. It involves the use of technology and problem-solving skills to develop working data models and manage databases.  

Summing it Up:

Data engineering refers to managing and storing data. In today’s modern era data is like the fuel for every industry. Managing such a huge amount of data is a hectic process. Data engineers make it easy for industries to manage their data properly. Knowing the required skills like coding, data storage, cloud storage, etc. makes it easy for you to get a job in this field. Getting a proper certificate will boost your profile to the top. Managing your portfolio with good projects will highlight your resume. Having extra skills like reasoning, verbal and analytical, etc. will help you land a job in top companies. Hopefully, this article will answer all your queries related to data engineering and have given you a fair idea of how to become a data engineer!

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