How to Become a Data Engineer
Looking for a career with a competitive salary and excellent job growth expectations? Join the exciting big data industry or take the next step in your career as a data engineer. This information technology role allows you to work on data pipelines, databases and related systems. If you’re interested in collecting, managing and analyzing data, then find out how to become a data engineer today.
What Does a Data Engineer Do?
Data engineers perform many specific responsibilities and tasks. In general, the role requires you to work closely with big data. Many engineers work with data pipelines to ensure data is safely and efficiently gathered. Engineers also design and maintain databases for safe storage of data at scale. Finally, some work with data scientists and analysts to analyze and interpret the data for relevant decision-makers.
Data engineers work in government organizations, non-profit organizations and private businesses. Some are also self-employed and work directly with clients to design, build and manage data ecosystems.
Most of the work performed by data engineers is done on a computer. Many work in offices, though there are also a large number of remote work positions available in this career pathway. In some cases, data engineers are also responsible for training employees and collaborating with other professionals.
Types of Data Engineering Roles
Not every data engineer performs the same duties. Before finding out how to become a data engineer, it may be helpful to consider the area you’re most passionate about. Here are three broad categories of data engineering roles:
- Database engineers: These professionals work mostly or exclusively, on databases. You’ll want to be familiar with extract, transform, load (ETL) methods and be prepared to deliver table schemas while monitoring database efficiency.
- Pipeline engineers: Consider this type of role if you wish to work directly with one or more data pipelines. These professionals often work for larger companies where there are many large pipelines in the ecosystem.
- General data engineers: Many data engineers handle the entire data ecosystem or work collaboratively with a team of other engineers. If you aren’t sure which of the above roles best fit your career goals, it may be best to choose a general approach and learn about both roles.
How to Become a Data Engineer: The Data Engineer Career Path
Data engineering requires a broad range of complex skills, so many applications tend to focus on your abilities. The exact steps on learning how to become a data engineer can vary, but these are some basic ones that can help you compete for many positions in this growing field.
1. Earn a Relevant Degree
Popular degrees include software engineering, data science, math or business, according to the U.S. Bureau of Labor Statistics. Enrolling in a highly rated bachelor’s degree program will not only help you practice relevant skills but can also help you build a list of references in the industry.
2. Learn the Necessary Skills
You’ll need to know how to build, manage and test data architecture for this career. Some positions may not require a degree but may require you to pass a number of skills-based tests, so it’s important to be very familiar with the essential skills of the job before applying.
3. Start Working on Projects
Help make your application stand out by completing projects in the field. You can look for contracts for entry-level engineers, showcase work completed during your bachelor’s degree or even design your own data pipeline and database as part of your portfolio.
4. Start Applying to Data Engineering Job Openings
Data engineering is an exciting field but it can be a competitive job market. Refresh your resume and be sure to highlight relevant skills and experiences. Search for job openings in your desired area or remote positions that you qualify for. Be prepared for an interview, skills test or both.
5. Continue Your Education
The big data landscape is constantly changing. A career in information technology requires you to continue to learn about the latest advancements, updates and changes in the field. Data engineers must continue to learn more about their field, practice coding languages and be familiar with big data tool updates. You can consider a master’s degree in data engineering or a relevant field as part of your ongoing education.
Data Engineer Salary and Job Outlook
Expect competitive salary and growth opportunities for this in-demand career pathway. While salaries can range depending on years of experience and location, you may be qualified for a competitive wage in data engineering. Explore both the expectations and job outlook to see if a career in data engineering is a good move for you.
Because data engineering is a relatively new field, the U.S. Bureau of Labor Statistics (BLS) doesn’t include this career as a separate entry. It does, however, record the median pay and job outlook for database administrators and architects. The average annual salary in 2021 for these professionals was $101,000, according to BLS.
In October 2022, PayScale found the median salary for data engineers was about $94,000. Senior data engineers earned a median salary of approximately $125,000.
Job Outlook for Roles Related to Data Engineering
Database administrators and architects are expected to enjoy a faster-than-average job outlook change between 2021 and 2031. According to BLS, the number of these positions is expected to increase by about 9% over the decades.
Key Data Engineer Skills and Responsibilities
Learn the essential skills of the job to be confident in your abilities as a data engineer. While the position can vary, here are some core skills that you’ll likely use on a daily basis:
- Structured query language (SQL)
- Cloud computing
- Extract, transform, load (ETL)
- Additional workplace skills
Explore each of these categories to learn how to become a data engineer. Most bachelor’s degree programs in data engineering or related fields will include training in these areas, though you may need to learn some skills outside of your degree program.
Structured Query Language
Structured query language (SQL) may be one of the more important skills for data engineering. Consider practicing syntax, commands, use-cases and other features of SQL and be prepared to use these skills daily in most positions in this career.
SQL can be used to find insights and interpret data. While there are other languages that can perform some of the duties of an engineer, SQL is the preferred language for most companies.
Cloud data engineers primarily use cloud computing service platforms. Platforms like Google Cloud Platform, Amazon Web Services and Microsoft Azure can help companies move to cloud-based operations. An engineer, or team of engineers, often leads this transition and ensures optimized cloud computing. These platforms are similar but have important distinctions, so you’ll want to be familiar with each and up-to-date on recent changes.
Extract, Transform, Load (ETL) Tools
Working on data pipelines requires ETL tools. These tools are crucial for database administrators but are also frequently used by engineers. There are different tools available, such as Star and Snowflake, that are useful when learning how to become a data engineer.
Using these tools, you can extract data from where it lives using appropriate security controls. Next, you can transform the data to ensure optimized information is stored in the database. Finally, you can load the data into your chosen warehouse or data lake.
SQL may be the most common language, but many more can be useful in your data engineering position. Python, R, C#, Scala and Java are some of the more popular options. Discuss which languages are most common in your area or in your chosen specialization of data engineering.
Learning a programming language can take some time, so be sure to prioritize it in your training. Most bachelor’s degree programs offer classes in at least one of the above languages to help you prepare for your career.
In addition to all of these specific, technical skills, you may use the following workplace skills as you learn how to become a data engineer:
- Data-driven thinking: You’ll be working with numbers, so you need to keep a clear head about the best course of action after reviewing the data.
- Ability to collaborate: Some data engineering positions are as part of a team of engineers and most engineers need to work closely with data scientists.
- Attention to detail: A small error can delay processes, compromise data and alter designs. Attention to detail is a key skill for anyone working in big data.
- Self motivation: Some positions require you to work on your own, particularly remote positions, so you’ll need to remain on task and on schedule by yourself.
Data Engineer Responsibilities
The daily responsibilities of a data engineer can vary depending on the work environment. Most of these professionals perform many or all of the following tasks:
- Develop data architecture: One or more data pipelines need to bring together information in accessible, secure databases. Both of these architectural elements need to be specific to an organization and its goals.
- Test data pipelines: Engineers test batch time and data quality to ensure efficient operations.
- Structure and consolidate data: The data itself needs to be structured and consolidated to prepare for efficient storage. This also makes it more convenient for data scientists to analyze it.
- Monitor and maintain databases: Any inefficiencies, insecurities and other issues need to be safeguarded against. In the event of a database issue, engineers need to work quickly to restore normal operations.
- Optimize the entire big data ecosystem: In addition to all of the above tasks, engineers are often required to consider other optimization strategies for the entire big data ecosystem. This task could include minor adjustments or major strategy shifts.
Data Engineer Requirements in Education
A bachelor’s degree in data engineering is a competitive step to launching your new career. Some applications don’t require you to hold a degree in a relevant field, so you may also apply to become a data engineer with the right skills and experiences. Explore the bootcamps, short courses, bachelor’s degrees and graduate degrees that may strengthen your application or advance your career.
Bootcamps and Short Courses
Online bootcamps and short courses offer skills-based training in your industry. You can also find similar short courses on many college campuses. While these programs don’t offer a degree, some offer a certificate of completion that may improve your application. They generally focus specifically on the skills you need for a career in data engineering, leaving out general education requirements.
A bachelor’s degree in data engineering or a related field can be a common educational requirement for a position in this industry, according to the U.S. Bureau of Labor Statistics. You can usually complete a degree in four years, though some programs allow you to complete it in three years.
As you search for data engineering degrees and learn how to become a data engineer, consider the fields of computer science, physics or applied mathematics. These degrees can include programming languages and related skills.
Consider a master’s degree in data engineering to expand your possibilities. While not required for many entry-level positions, a master’s degree can be a competitive choice. Most degrees dive deeper into programming skills, theory and data systems. Master’s degrees are offered both online and on-campus by a number of public and private colleges around the nation.
Data Engineer FAQs
Is a Data Engineer a Good Career?
The number of jobs related to data engineering, such as database architect, is expected to grow faster than average by 2031, according to BLS, though BLS data doesn’t include specific information on data engineers. This career has a median pay that’s higher than average among careers in the United States.
How Long Does It Take to Become a Data Engineer?
The most common requirement for becoming a data engineer is a bachelor’s degree, which typically takes four years to complete. You may be able to earn your degree in three years and some positions only have skill-based requirements rather than requiring a degree.
What Is the Difference Between a Data Engineer and a Data Scientist?
Data engineers mainly develop, construct, test and monitor data architecture. Data scientists, however, generally clean, organize and analyze the data. Both positions work in big data, and duties can overlap depending on the work environment.