How to Get Started
as a Big Data Engineer

Refine Your Skills and Remain Relevant

Big data engineering is a data science branch that focuses on developing systems to optimize the data collection and analysis process. Due to companies’ increasingly high volumes of data, this has become an in-demand profession.

In this guide, we will discuss how to become a big data engineer. We’ll look at whether you need a Bachelor’s Degree in Computer Science or Data Science. We’ll also cover the required big data engineering skills including programming languages and big data analytics.

What Is a Big Data Engineer?

The role of a big data engineer is to test and optimize a company’s data infrastructure and data pipelines. These highly-skilled data professionals develop and improve systems to help employees have better access to an organization’s relevant data.

A big data engineer is sometimes just called a data engineer. With the rapid advancement of big data frameworks and databases, data engineers have needed to upgrade their skills to work with large data lakes and systems.

How Does Big Data Engineering Relate to Data Science?

Big data engineering plays a huge role in the field of data science. Data science consists of collecting, organizing, scraping, and analyzing data to extract meaningful insights from raw data.

To do this, data scientists and data analysts need to have a streamlined big data infrastructure. This is where data engineers come along. Their role makes their jobs more straightforward by implementing techniques to improve the data infrastructure. They transform varied sources of data into structured data that can be used by data scientists.

How Long Does It Take to Become a Big Data Engineer?

It takes at least four years to become a big data engineer. You will need to have a Bachelor’s Degree in Data Science, Computer Science, or another related field. Additional degrees, internships, or certifications may take another few years to complete.

Some roles expect you to be professionally certified before you can apply. Certifications require a certain amount of experience in data science before you can qualify for them. Most require you to have one to three years of experience.

Where to Study Big Data Engineering

You can study big data engineering at a community college or university, or online through a bootcamp or online course. Which route is best for you depends on your previous education and experience, and your career goals.

If you are taking the first step in your journey of becoming a big data engineer, you should consider pursuing a Bachelor’s Degree in Data Science. However, if you already have some background in data science and you’d like to specialize in big data, a course or bootcamp could be a quicker and less expensive option.

Big Data Engineering Community Colleges

You can earn a certificate or Associate Degree in Big Data Engineering at a community college. Community college is a more affordable and accessible option than a four-year university degree. Certificate programs take between three months and a year to complete. Associate degrees usually take two years to complete.

The College of San Mateo, for example, offers a big data certificate program designed to help you enter this profession. This program covers topics like data warehousing, R programming, and NoSQL Databases.

Big Data Engineering Universities

A bachelor’s degree is the most common first step towards becoming a big data engineer. Most universities offer four-year bachelor’s degree programs. You can also pursue a Master’s Degree in Data Science or Data Engineering. A graduate degree will open doors to higher-paying senior positions.

Big Data Engineering Coding Bootcamps

Another great path to becoming a big data engineer is to join a coding bootcamp. Coding bootcamps can prepare you for a variety of different subjects, including big data and data engineering. They are short-term courses that give you real-life skills.

Big Data Engineering Online Courses

Online courses are a good idea if you already have some background in programming or data science. They are a great way to develop your knowledge of more advanced concepts like big data and NoSQL databases.

How to Become a Big Data Engineer A Step-by-Step Guide

How to Become a Big Data Engineer: A Step-by-Step Guide

To become a big data engineer, you need a blend of educational training and work experience. It’s also a good idea to earn a certification to showcase and validate your skills. Below is a step-by-step guide to getting your first role.

Earn a bachelor’s degree

The first step to becoming a big data engineer is to earn a bachelor’s degree. It could be in data science, computer science, or any other IT-related field.

Get a specialization in big data or data engineering

After getting your bachelor’s degree, you’ll typically obtain a master’s degree or diploma in data engineering or big data. This will allow you to focus your career on a big data engineering path.

Work on your first projects

The next step is to gain some work experience, either through your own projects or by applying for freelance jobs or internships. Some universities, colleges, and boot camps offer job help or internship opportunities.

Obtain a certification

This is an optional step, but will go a long way to distinguish yourself from other potential candidates. Earning a certification is a great way to authenticate and demonstrate your data engineering skills.

Submit your resume

Now you have the required skills and training to work in the field, you can start submitting your resume. Check with your school or education provider to see if they provide application and interview support.

Entry-Level Big Data Engineering Job Requirements

To work in an entry-level data engineering position, you must have industry-specific skills such as R programming, SQL, NoSQL Databases, and data collection. You’ll also need to be an excellent problem solver, critical thinker, and communicator.

Big Data Engineering Salary and Job Outlook

According to Payscale, the average salary for a big data engineer $129,498. This is significantly higher than the average wage of $56,310 for all occupations according to the Bureau of Labor Statistics (BLS).

The job outlook is promising too. Although BLS does not have an estimated growth rate specifically for big data engineers, it reports that the demand for database administrators is expected to grow 10 percent between 2019 and 2029. This is significantly higher than the average employment growth for all occupations, which is four percent.

Example Big Data Engineering Job Interview Questions

  • Explain what data pipelines are.
  • Do you know the differences between the types of data design schemas?
  • In your own words, define data modeling.
  • Name the components of the Hadoop application.
  • What are the differences between structured and unstructured data?

What Does a Big Data Engineer Do?

A big data engineer’s main responsibility is to make data accessible to all relevant users. They also develop data applications, and systems to streamline data collection and analysis. Below are the main day-to-day job duties you can expect.

Process Raw Data

Data collection and processing is a large part of the role. You’ll be responsible for finding different sources of relevant raw data so you can allocate all data into one single warehouse. This makes it easier for employees to access structured data.

Develop Data Applications

Another primary task is to design and develop data applications. You will write scripts and SQL queries. You’ll also use different data-backed programming languages like SQL and R to build scalable and organized data-driven applications.

Analyze Data

You’ll also work with other IT professionals to analyze the collected data in order to make business decisions. You’ll help extract meaningful insights out of raw data and improve the processes that enable this to happen.

Essential Big Data Engineering Skills and Certifications

Essential Big Data Engineering Skills and Certifications

To work as a big data engineer, you need to have certain skills in SQL and R programming, data collecting, and data analysis. You must be able to work with platforms like Microsoft Azure, and NoSQL Databases. Below we will look at the essential skills in detail and the certifications you should get to stand out from other candidates.

Big Data Engineering Skills

Microsoft Azure

Microsoft Azure is a cloud-service platform that works as an Infrastructure as a Service (IaaS). It is used for machine learning, virtual computing, artificial intelligence, analyzing big data, and computer engineering. As a big data engineer, you must work with Microsoft Azure because it’s an essential data storage platform used for big data analytics.


Most data engineering tasks require programming skills. You will develop a data-driven infrastructure and tools to optimize the data processing dynamic. You will use your programming skills for data warehousing, data modeling, and building pipelines. You must be competent in using programming languages like R and SQL.

Data Processing

Another essential skill is data processing. You must be able to collect, filter, and analyze data. This will allow you to develop better systems and data management tools for other users.

Big Data Engineering Certifications

There are a few well-known professional certifications that demonstrate your data engineering skills. Some of the most reputable certifications are the Google Professional Data Engineer and the IBM Certified Data Engineer. You can find out more about these credentials below.

Google Professional Data Engineer

This is one of the most reputable data engineering certifications. The Google Professional Data Engineer certification measures your ability to build and design data processing systems and machine learning models.

There isn’t any official prerequisite, but the provider recommends candidates to have more than three years of experience in the field. The exam fee is $200, and it lasts around two hours. You can take the exam online or in person.

IBM Certified Data Engineer - Big Data

This IBM Data Engineering certification focuses on big data and artificial intelligence. This certification covers different skills like cluster management, network requirements, BigInsights, BigSQL, Hadoop, and Cloudant (NoSQL).

You must also be competent in other skills like machine learning and data governance. To apply for this certification, you must first pass the IBM data engineer exam.

Microsoft Certified: Azure Data Engineer Associate

Microsoft Azure is a crucial element of many data engineering roles. That’s why this certification in Azure data engineering is extremely relevant to anyone pursuing a career in big data engineering. This credential measures skills like data security, data processing, data storage, and monitoring.

You must be able to work with programming languages like SQL, Python, or Scala. You need to pass the certification exam and pay the $165 fee to receive this certification.

Reasons to Become a Big Data Engineer in 2021

Like most data science-related careers, big data engineering is in demand in 2021. Most companies have a large set of raw data that needs organizing. This means you’re likely to have a diverse range of job opportunities as a big data engineer.

Big data engineers enjoy high salaries and job growth opportunities. You must first be prepared to spend years earning the relevant education and training. However, if you’re looking for a data science career with great prospects, this might be the profession for you.

Big Data Engineering FAQ

What do you study in big data engineering?

When studying big data engineering, you’ll learn about cloud computing, software engineering, data science fundamentals, statistics, and math principles. You will also learn about programming languages like R, Python, and SQL.

Is big data engineering hard?

Big data engineering is a complex job that requires critical thinking and logical skills. It also involves repetitive tasks across the development process. You should only become a big data engineer if you’re prepared for this type of rigorous work.

Who earns more, data scientists or data engineers?

Although data engineers and data scientists have very similar responsibilities, they have slightly different average salaries. According to Indeed, data scientists earn $120,051 per year and data engineers make an average of $129,498.

Can I become a data engineer with no experience?

Yes, you can become a data engineer with no experience. However, you must receive some kind of data science training, whether it is a Bachelor’s Degree in Computer Science or Data Science, an online course, or a coding boot camp.

Find the best data science bootcamps to get you hired.


Get matched to top data science bootcamps

By continuing you indicate that you have read and agree to Study Data Science Privacy Policy

Powered By
Career Karma



You don't have permission to register