How to Become a Data Engineer: Steps, Skills, & Salary

Data engineering is a relatively new field that involves building and maintaining data structures for organizations. Learn about becoming a data engineer.

portrait of Juliann Scholl, Ph.D.
by Juliann Scholl, Ph.D.

Updated November 4, 2022

Edited by Cameren Boatner
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How to Become a Data Engineer: Steps, Skills, & Salary
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Data engineers source, clean, and transform raw data to make it usable and understandable for other data teams in a company. But they don't just put their heads down and mine through data all day — data engineers also work with other teams and help teach their companies how to use data more efficiently.

If this sounds like something you're interested in, read on to learn how to become a data engineer.

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Ready to start your journey?

What Is a Data Engineer?

Data engineering combines data science and software engineering. Data engineers advise companies on how to improve their data use, maintenance, access, and storage.

These professionals analyze and aggregate large data sets to help organizations make better operational decisions. Data engineers can also use data to improve how equipment and machines function, and they know how to integrate new data management software into currently existing systems.

What Are Key Data Engineer Requirements and Skills?

Most successful data engineers possess the following skills:

Data Engineer vs. Data Scientist

Data engineers' and data scientists' work differs primarily in concentration and approaches to solving problems. Data engineers focus on data architecture and building infrastructure to provide information. Data scientists use statistical analysis and advanced mathematics to answer questions.

How to Become a Data Engineer

To become a data engineer, you'll need to learn and develop expertise in various processes and applications. You'll also most likely need a postsecondary education, accumulated experience, and a portfolio.

Step 1: Learn the Fundamentals of Data Engineering

If you're interested in data engineering, you can start building your skills now. Managing and creating database systems requires programming language proficiency. Prospective data engineers should learn SQL, a common language that enables data storage. You should also master Python, Spark, Hadoop, and Kafka, which prove helpful in statistical analyses and modeling.

You can start teaching yourself the fundamentals of data engineering online to see if it's something you really want to invest your time and energy in.

Step 2: Earn a Bachelor's Degree or Get Certified

Some employers prefer job applicants with bachelor's degrees. Some college majors that can prepare you for data engineering jobs include:

Acquiring the proper skills and work experience can benefit individuals without bachelor's degrees. If you have a background in data or a similar field, you might be able to get a data engineer job with a certification.

Credentials likeGoogle Analytics andcertified computer progressional (CCP) data engineer certification from Cloudera can prove valuable to employers.

Step 3: Get Hands-On Experience in Data Engineering

To become a data engineer, you'll need relevant work experience to show growth in specific skills. Seeking opportunities to showcase proficiencies in SQL, Python, and other programming languages will be beneficial. If you're transitioning to data engineering from another field, you should show experience with algorithms, coding, or data management.

If you're in college or a recent graduate, an internship can help you build a portfolio of projects. Internships allow you to hone your skills in applied settings. Also, document projects you complete through your coursework.

Step 4: Start Applying for Data Engineer Jobs

After securing an entry-level position and growing your skills for a year or more, you're probably qualified for data engineering jobs. Some of the best employers offer skills development, continuing education opportunities, and career advancement.

Keep in mind your long-term career goals when applying for data engineering jobs. For example, you might be interested in pursuing a managerial position after working in entry-level positions.

Step 5: Keep Building Your Portfolio

Your portfolio should display your skills — and you should constantly be updating it. This document functions as an extended resume. Data engineers need to keep their portfolios current — giving an out-of-date portfolio to prospective employers can hurt your job prospects.

Besides core and specialized skills, data engineering portfolios should typically include education, certifications, and work experience. You should also list past projects that illustrate your expertise and proficiency in a few key areas. You can also include projects from relevant coursework and internships in your portfolio.

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How to Find Data Engineer Jobs

There's no one way to find data engineer jobs.

Some individuals take a relatively direct path to data engineering through internships and bachelor's degrees. Others might find their way to this occupation after working as data scientists, software engineers, or data analysts. Given the novelty of this field, many professionals acquire certifications or switch careers to obtain data engineering jobs.

What's the Average Data Engineer Salary?

Data engineers generally enjoy high salaries compared to professionals in other industries. According to Payscale, data engineers earned an average annualsalary of $93,570 as of October 2022. Data engineer jobs in California, particularly in the San Francisco area, pay about 31% more than the national average. Other high-paying states include New York and Washington.

Data engineers can increase their earning potential by changing employers, moving to locations with higher-paying positions, or obtaining managerial positions. You can also earn a higher salary with a graduate degree.

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