Data engineers work closely with scientists and other professionals, using data modeling and warehousing to capture, store, and evaluate diverse data points. Learn more about this in-demand engineering track, how data engineers use data to build pipelines and organize data structures, and what steps are required to earn a data engineering degree.
Data Engineering Degree Program Overview
A master’s degree in data engineering prepares you for the complex tasks of designing, monitoring, and structuring databases and data flow. This program also helps you understand the key skills required to achieve these goals. In an advanced degree program, students can pursue roles in research, education, or hands-on work with other data scientists and engineers.
Data engineering degree programs often include a range of courses and hands-on experiences that instill the knowledge you need for a data engineering career. Some institutions offer online data engineering degree programs, giving you more flexibility in choosing the best course for your specific goals. Other programs provide hybrid studies, balancing the flexibility of online courses with the hands-on experience of in-person classrooms and labs.
While a bachelor’s degree may be all that’s required for some data engineering jobs, a master’s degree offers more specialized training and can improve your job application. Data engineers must constantly learn and grow as the industry changes, so ongoing education is an excellent way to move forward in this fast-paced career.
What Is Data Engineering?
It’s easy to confuse the roles of data scientist and data engineer. While a scientist works closely with an engineer to make sense of the data, the engineer is the one who works to design efficient pipelines. This distinction means that a data engineer typically spends more time finding ways to collect and store information. These skills are crucial to helping businesses make the most of big data to grow and serve their customers.
Designing a Data Pipeline
One of the most important tasks of a data engineer is to design and improve data pipelines. The number of pipelines and the data being collected will vary based on the company, but all pipelines can fall into four tasks:
- Ingesting: Engineers find the best ways to gather data, including selecting data sources and helping input that data into the pipeline.
- Processing: Big data needs processing to prepare it for analysis. Data engineers must find ways to make sense of countless information points to arrive at a useful data set.
- Storing: Massive amounts of information need massive amounts of storage space. Warehousing data in safe, easy-to-retrieve locations is another key step in a pipeline.
- Accessing: Finally, engineers must make data more user-friendly for customers and data scientists.
Preparing Data
The goal of an efficient pipeline is to capture relevant data and prepare it for analysis. Then, data engineers ensure that the information traveling through it flows smoothly. Data scientists, business owners, and decision-makers don’t have time to sift through multiple warehouses and countless data points, so it’s up to an engineer to manage data, develop tools, and prepare data sets.
Benefits of Earning a Data Engineering Degree
Why study data engineering? A master’s degree in data engineering can be a competitive career option whether you’re working in the field or searching for your first job as an engineer. Remember to consider both benefits of earning a data engineering degree to see if it’s the right step in your career.
Career Growth
While there are many certificate and bachelor’s degree programs in the field, a master’s degree is an advanced option that helps promote even more specialized skills. It’s a competitive option for anyone looking to grow in their field. Once you earn the master’s degree, you may be able to negotiate a raise or promotion due to your additional skills and experiences.
Change of Career
Other students pursue a data engineering master’s degree to change jobs. Consider this degree choice if you already hold a bachelor’s degree in a science, engineering, technology, or math field and wish to become a data engineer. Moving from a data scientist to a data engineer can be a great way to move up in your industry and negotiate a higher salary.
What Can You Do With a Data Engineering Degree?
The specific tasks you’ll take on depend on the industry you choose and the size of your company. Some professionals work with large teams to analyze many data models and pipelines to ensure they are optimized and ready for analysis. Other engineers work on their own to design pipelines and monitor data collection.
As a data engineer, you’ll need to be familiar with programming, software engineering, software architecture, cloud platforms, and data modeling techniques. Some professionals choose a particular area of big data to specialize in, while others perform various daily tasks.
Data Engineering Salary and Job Outlook
Data engineers, also known as database administrators and architects according to the U.S. Bureau of Labor Statistics (BLS), can expect a competitive salary and faster-than-average job growth throughout the coming years. You’ll want to explore both features as you consider a career in this exciting field. While a master’s degree isn’t generally required for a data engineering position, it can be a competitive choice as you look for ways to negotiate a higher salary.
Salary
According to BLS, the 2021 median pay for these professionals was $101,000 per year. The highest 10% of professionals in this career earned over $169,500 in 2021, while the lowest 10% earned less than $63,260. By state, the highest annual income was in California, New York, and Virginia. Salaries also vary based on employment type, years of experience, and other factors.
Job Outlook
The job growth outlook is estimated to be 9% between 2021 and 2031, which is faster than the average job growth expected across the decade. The largest employers of these professionals are in the finance, insurance, computer systems, and information industries. Educational services and companies in other fields also employ data engineers.
How Much Does a Data Engineering Degree Program Cost?
The cost of a master’s degree in data engineering can vary depending on the program, location, and other features. Most programs cost between $13,000 and $90,000. Luckily, many scholarships, grants, and assistantship programs can reduce the tuition cost or completely cover the cost of your program. Be sure to compare in-state and out-of-state tuition rates as you select your program.
Data engineering programs also vary in length. In general, it takes two to three years to complete a master’s degree as a full-time student. Consider part-time options if you wish to continue to work as you study, or look for online programs that offer flexible scheduling.
Data Engineering Scholarship Information
Scholarships can be based on financial needs or academic achievement. In most cases, a scholarship allows you to pay for tuition or other expenses without worrying about paying the amount back. Here are some popular scholarship sources:
- School: The program you’re interested in attending may offer scholarships. Check for needs-based or achievement-based options for incoming students.
- Employers: If employed, your current employer may offer tuition reimbursement for you to further your education. This is particularly popular if you currently work as a data engineer or in a related position.
- Charitable organizations: Local non-profit groups, national organizations, and other charitable institutions may offer scholarships for your situation.
- Government: Look for federal, state, and local assistance to help pay for your master’s degree.
Some scholarships cover the entire cost of your program. Most, however, offer a few hundred to a few thousand dollars to help cover your expenses. Applications can also include essays, interviews, and questionnaires, so be sure to start your scholarship search early.
Assistantships
Some master’s degree students pay for part or all of their program costs through assistantships. As you explore courses, look for teaching or research assistant options, but be sure to review all requirements; these programs usually require you to set aside time to work as you study, either in a lab or classroom setting.
An assistantship also comes with funds to pay for your program, and it can be an excellent hands-on experience as you prepare to be a data engineer.
Data Engineering Program Requirements
As an advanced degree, a master’s in data engineering requires a bachelor’s degree along with specific skills and experiences. You don’t need a bachelor’s degree in data engineering, although you should have one in a related field. Common fields include data science, computer science, applied math, and statistics.
Skills to Become a Data Engineer
Becoming a data engineer requires attention to detail, a passion for exploring big data, and the ability to collaborate with other data professionals. Students must also be familiar with several specific industry skills. While the skills can vary, here are some common areas you’ll need to be experienced in to become a data engineer:
- Operating systems: Expect to work in Windows, Linux, UNIX, Solaris, and other operating systems.
- Coding: While you might not need to be a master of coding, you may need to understand Python, Java, C# or other coding languages. You’ll likely brush up on these skills during your master’s degree courses, but many programs expect you to be familiar with coding before enrolling.
- Data architecture and warehousing: Master’s degree programs typically expect at least basic knowledge of warehousing and data architecture. You may have covered these areas in your bachelor’s degree program or on the job in a related field.
- SQL: This is perhaps one of the most fundamental skills for data engineers. Issuing optimized queries and exploring extensive query lists are everyday tasks in this role.
Application Process
Connect with one or more of your favorite programs to learn more about the specific steps of the application process. While they vary, here are the most common steps:
- Bachelor’s degree: Most master’s degree programs require you to have completed a bachelor’s degree program in a related field.
- GRE: The Graduate Record Examination is required for some master’s degree programs. You can, however, apply to many programs and earn a degree without taking this standardized test.
- Application: You’ll need to fill out an application to apply. This may include a fee. Some institutions only accept applications during a specific window of time, while others offer rolling admissions. You may also need to include an essay describing your background and/or career goals.
- Interview: For some programs, you’ll be invited to an interview to discuss the program. Similar to a job interview, it’s important to prepare answers for this step and consider why you would be a good fit for a particular program.
The application timeline varies widely. Some highly rated schools can take months to decide about an application, while others require only a few hours. You can find and complete most applications online.
Common Courses in Data Engineering Degree Programs
Data engineering master’s degree programs can include diverse data-related coursework. Some programs allow you to concentrate on a specific field area, while most offer an overview of the entire industry. Here are some common courses you can expect to take as a student of data engineering:
- Machine learning
- Data mining
- Data visualization
- Database systems
- Network security
- Business analytics
Many master’s programs end in a capstone project. This hands-on project is personalized and designed to showcase the skills you learned during your program.
How Long Does It Take to Complete a Data Engineering Degree Program?
The program length depends on your previous experience and the type of program you choose. If you don’t have a bachelor’s degree, you may need to obtain that first before applying to a master’s degree program. This would take approximately four years to earn a bachelor’s degree and between two and three years to earn a master’s degree.
If you already have a bachelor’s degree in data engineering or a related field, you may be able to complete your degree in as little as one year. Accelerated master’s programs can take between 12 months and two years to complete. Part-time master’s degree programs can take up to six years.