Find Online Data Engineering Programs
Last Reviewed/Updated: February 5, 2021
In order for those within data science to use their mining tools and analyze information, there must be a foundation to work with. When it comes to gathering data and managing databases, these are duties reserved for data engineers within the organization. Duties in this career include creating the infrastructure, looking out for any errors, and keeping things optimized to make the analyst's job easier. With the foundational responsibilities needed, there are a number of high-paying opportunities in the workforce.
Featured Online Data Science Programs
Johns Hopkins AAP
|MS in Data Science and Policy||Website|
George Mason University
|Master of Science in Data Analytics Engineering||Website|
Northern Illinois University
|Master of Science in Data Analytics||Website|
|MS in Business Analytics||Website|
|MS in Data Science||Website|
Data Engineering Degrees
One of the growing opportunities within data science is pursuing higher education online. This is a convenient way to gain experience on skills such as structuring data, managing data, and learning programming while maintaining a job.
Online Data Engineering Programs
Many online programs provide an asynchronous experience, meaning students can watch lectures and participate in class discussion boards on their own time. Typically, there will be requirements to submit assignments or complete quizzes and exams in order to prove achievement throughout the course.
Online Masters in Data Engineering
Especially when pursuing a Master's degree, many programs are geared toward part-time students that take one to two courses each term. If full-time programs are still too time-consuming, there are alternatives in graduate certificates or vendor certifications.
Featured Online Data Science Programs
|MS in Data Science||Website|
Notre Dame of Maryland
|M.S. in Analytics||Website|
|Master of Data Analytics Leadership||Website|
|Master of Science in Business Intelligence and Analytics||Website|
Saint Joseph’s University
|MS in Business Intelligence & Analytics – Data Analysis||Website|
Graduate certificates can be truncated forms of data science programs, or they will take portions of the core curriculum and various electives. Vendor certifications through companies like Oracle, Microsoft, and Cloudera, will show competence with using a specific tool set.
An example of obtaining a vendor-based credential is completing the Cloudera Certified Professional Data Engineering exam. This provides a series of problems that requires many skills in gathering and manipulating data within a distribution Hadoop cluster, and 70 percent of the exam must be correct in order to pass. Retakes are allowed 30 days after completion if failed, and there is no limit on retaking the exam until passing, but there is a fee that has to be paid each time.
Specific Programs in Data Engineering
When looking for degrees, careers in data engineering can be achieved by pursuing programs in data science, computer science, and engineering. When browsing Master's degrees, some data science programs will have concentrations directly in data engineering, or there could be engineering degrees with an emphasis in data or computer science. Elective courses should have a focus on creating database architecture or design, and management of data.
For example, Merrimack College in Massachusetts has an online Master in Data Science program with a curriculum developed by the School of Business and the School of Engineering. The program has eight courses and takes anywhere from 7 months to 16 months to complete. Courses along the engineering track are foundational overviews of data management and statistical analysis.
Johns Hopkins University in Maryland has an online Master of Science in Data Science offered by the Whiting School of Engineering has a number of electives to customize the degree. Students must take either Principles of Data Systems or Introduction to Machine Learning within the core curriculum, and electives include Large-Scale Database Systems and Big Data Processing Using Hadoop.
Prerequisite Education for Data Engineering Degree Programs
To break into a career in the data engineering field, at least a Bachelor’s degree is needed within the field of software engineering. At the very least, coursework should be completed in database management, software design, and computer programming. This holds true when looking into further education for a Master’s degree. Many data science programs will require prerequisites in topics like linear algebra, statistics, probability, calculus, and having proficiency in a programming language like Python or R.
For the Data Science and Engineering program at the City College of New York, there is a requirement of at least two semesters of calculus, probability, and statistics, along with credit in linear algebra and programming – preferably Python. Admission into the online Master of Data Science at the University of Denver requires coursework in calculus, linear algebra, and statistical analysis.
In order to gain entry into a Master’s program, other requirements typically include letters of recommendation, a personal statement that details experience and goals, and GRE test scores. Sometimes, the latter is either optional or can be waived with at least a 3.0 cumulative GPA or a significant amount of work experience. Online programs will vary greatly in admission periods. Some will only accept students in the fall or spring term, while others that break things up into an eight-week course structure can allow students into the program between four to six times a year.
There are generally no prerequisites when taking vendor-based certification exams (such as Microsoft, Amazon, and Coursera), but it is highly recommended to take some courses as these exams will have a fee per attempt. There are higher levels of skills that can be obtained that will require completion of prior certification. Some certification methods have coursework available in a self-paced format, or students can pay an additional fee for an instructor-led session. Requirements for graduate certifications at universities will typically be the same as admission needs to get into the Master’s program.
Typical Data Engineering Courses
It is important to note that coursework within data engineering should have an emphasis in subjects such as database architecture, administration, mining, and systems analysis. The goal for an engineer is the development of the systems and processes that are used, not to analyze trends and predictive models. This is what separates data engineers from the traditional data scientist.
Master’s degrees will have courses that focus on administration or development, providing students with the skills needed to help maintain an information technology database. They will learn fundamental tasks such as modifying the process when implementing new products and software, storing and recovering backup information, and protecting the data from outside sources and hacking attempts. Engineering education also includes the tools necessary to develop the applications that a company uses internally to access the database.
Iowa State University offers a Master of Engineering in Computer Engineering, which can be completed fully online. Example courses from the 30 credit curriculum include Advanced Protocols and Network Security, Legal and Ethical Issues in Information Assurance, Distributed Systems and Middleware, and Advanced Data Storage Systems. These provide skills in securing information, maintaining high-level systems, and “middleware” refers to the authentication and management of data to the applications and users.
At the College of Engineering at Northeastern University, there is a Master of Science in Data Analytics Engineering that presents a hybrid curriculum of analytical and engineering skills. Core courses include: Engineering Probability and Statistics, Data Mining in Engineering, and Data Management and Database Design. Electives that are geared more toward engineering skills include Big Data Architecture and Governance, Discrete and Data Structures, Information Retrieval, and Data Mining Techniques.
Data Engineering Scholarships and Assistantships
For students that have shown outstanding academic work prior to entering an undergraduate or graduate program, there are various scholarship opportunities to apply for. Many programs themselves will offer an internal scholarship for those just enrolling into specific programs. For example, Arizona State University provides the AFCEA Educational Fund that is open to any full-time undergraduate or graduate student in the College of Engineering at the university.
Frequently, more internalized scholarships will not even require an application process as admittance into the program counts. Otherwise, many scholarships are sponsored by individuals that are specifically for various demographics, such as location or minority representation to boost inclusion within the university, and they will require either high academic merit or demonstrate their financial needs, Some scholarships will require a paper describing why they would benefit from the award.
Some examples of scholarships specifically in data engineering include the IEEE Women in Engineering scholarship at UC Berkeley, which gives up to $7,500 in tuition for members of the organization with at least a year-long tenure. At USC, there is a specific dean’s scholarship for full-time students that are pursuing a Master of Science in Computer Science at the Viterbi School of Engineering. Graduate students at Nova Southeastern University that are enrolled in the College of Engineering and Computing and are employed by the federal government can receive an award up to $2,000 with the Edward Lieblein Memorial Fund Scholarship.
Assistantships provide an opportunity for successful students to become a teaching assistant or to complete a research project at the university. Essentially, they will help faculty and receive a stipend, along with the potential for lowering their tuition. Becoming an assistant as an undergraduate provides work experience and boosts networking opportunities, not to mention the potential for getting an academic job.
Stipends are generally offered on a monthly basis or for each term. In some cases, especially for graduate assistantships, tuition can be fully waived based on the program. Some examples include the assistantship for data science graduate students at New Jersey City University, which will lower tuition and give $3,500 in a yearly stipend for 18 hours of work each week. At the University of Wisconsin La-Crosse, students that are taking at least five credits in the term and are pursuing a Master of Science in Data Science will receive reduced tuition with at least 14 hours of work per week.
Data Engineering Careers
Specialists in data warehousing manages data storage for an organization and its clients, protecting the information from outside parties. Some of their duties include optimizing the infrastructure and identifying any issues or problems that could arise in the future. Information they can manage can be a large variety of data based on the company itself and the clients they work with, as well as any suppliers and vendors.
Data architecture is another position that involves developing that storage and processing of big data. They are responsible for the foundational aspects, creating the way data moves around, how it is accessed, and how it can be recovered. Other duties include optimizing the process and implementing any updates when needed, especially when it comes to the security of data.
At minimum, both architects and warehousing specialists need at least a Bachelor’s degree and some analytical work experience. In some cases, these jobs and their duties can be combined based on the size of the organization. The biggest distinction between an engineering role and a scientific role is that the former works with the structure and does not analyze the data. On average, engineers will see higher salaries than analyst positions.
Data Engineer Salaries
In terms of salary, traditional data engineers with a few years of experience can see an average of $91,845 annually according to PayScale, with that range between $64,000 and $132,000 based on location. Within the senior level, data engineers make around $123,069, with that number getting up to $157,000. San Francisco, California, sees a significant jump in engineering salary due to the high costs of living, with Los Angeles and New York City right behind it.
Learn more about data engineer careers.
Payment will certainly be impacted by how much experience the worker has in software. Knowledge in Apache Spark, Apache Hadoop, and Amazon Web Services see at least a six percent jump on the competition. A number of popular companies that have higher salaries in the data engineering field include Amazon, Facebook, and Blizzard Entertainment. Amazon typically has thousands of jobs available worldwide at a given time, specifically in data engineering. The bulk of these jobs reside in their headquarters in Seattle, but there are many opportunities in New York City, East Palo Alto, California; Herndon, Virginia; Austin, Texas; and Nashville, Tennessee.