Data has rapidly changed the world. Thanks to modern computing power, the ubiquity of the internet, and the emergence of smart devices, government agencies and businesses can collect massive amounts of data. This data has infinite applications — from determining the number of cars passing through an intersection to scrutinizing the clicking habits of a certain age group on a social media platform.
But data doesn’t magically appear on computers. Data scientists use special software to extract and analyze it and determine how a business or agency can best respond. Even everyday apps and programs rely on data to function and thus need specialized software created by data engineers. If you’re interested in working with extensive data sets and applying your findings, you may want to learn how to become a data engineer.
What Does a Data Engineer Do?
Data engineers create the software and programming frameworks that manage data storage and manipulation by both internal data scientists and external users. If data scientists are astronauts, riding the space shuttle and performing experiments in orbit, then data engineers are responsible for building the shuttle and getting the experiments into space. In the real world, what a data engineer does is more complex than an analogy. Data engineers work with data scientists and others responsible for creating a pipeline specifically built to leverage data for an organization.
Using software and coding languages, data engineers design programs to draw data from various sources, sort it, and present it in concise reports that managers can interpret to make informed decisions. Data engineers also make systems designed to handle data search tools useful to consumers, businesses, and data scientists. For example, ride-sharing services need to access the data of every car in a specific area when a user requests a ride. Another example is a music service whose servers must have the capacity to stream millions of songs requested by millions of users at any given time. These types of services are able to perform their tasks thanks to data engineers.
Steps to Become a Data Engineer
Pursuing a high-level career as a data engineer requires a specialized education, including an advanced degree and specific certification. Here are the steps to become a data engineer.
Earn a Bachelor’s Degree
The first step toward becoming a data engineer is earning a bachelor’s degree in data science or a related field. Here, students learn how to collect, clean, and analyze data and then leverage their findings to prepare reports. They discover how to blend statistics and data technology to suit a wide variety of applications. In addition, they develop soft skills that will be crucial in their careers, including teamwork, communication, and critical thinking.
Gain Real-World Experience
The best way to build on skills and knowledge learned in a classroom is on the job. Some bachelor’s degree programs may offer internships, and after graduating, students should seek opportunities to practice in professional settings. An entry-level Data Engineer can begin their career as an IT assistant to gain further mastery with computer programming, building data structures, maintaining databases and software design. Employers that use data engineers extensively include manufacturing companies, insurance agencies, technology companies, marketing firms, nonprofits, and government agencies.
Challenge Yourself with Certifications
While a college degree provides a strong foundational knowledge, there are several professional certifications that further show prospective employers that job candidates are qualified to take on the responsibilities of advanced data engineering roles. Reaching senior level Data Engineer status usually requires several years of building and managing intricate and secure data structures. They also can train junior hires and build infrastructures to mine and assess quality data that can direct business operations.
Get an Advanced Degree in Data Science
After earning a bachelor’s degree, there are several options for advanced education. Oracle, Microsoft, Amazon, and other major technology companies offer certification courses and tests to ensure that data engineers have the requisite competencies. These certifications aren’t required to work in the field, but employers may consider them valuable.
Many aspiring data engineers pursue an advanced degree, such as a Master of Science in Data Science. These graduate programs often feature project-based coursework, with courses in machine learning, SQL and NoSQL databases, big data analytics, and more. As a result, the curriculum provides graduates with a well-rounded education in data science.
Education is one highly relevant factor in determining what a data scientist’s salary. Those with a graduate-level degree in data science will find a plethora of job opportunities in lucrative sectors like finance, insurance, professional services, and IT.
Data Engineer Salary
The U.S. Bureau of Labor Statistics (BLS) includes data engineers in the category of computer and information research scientists. This master’s-level group of career options had an average salary of $118,370 in 2018. Those with the highest median annual salary, according to the BLS, worked as software publishers ($140,200).
Employment Outlook for Data Engineers
Data engineering is a thriving field, and the continued proliferation of data means the job market for data engineers should remain strong. The BLS projects the employment of computer and information research scientists will grow 19% between 2016 and 2026, creating 5,400 jobs domestically. Computer systems design and related services will see a massive 37.8% growth, with 2,100 of the new jobs coming from that segment of the industry. Research and development in the physical, engineering, and life sciences will add 1,700 jobs — a 35.5% increase.
Take a Look at Becoming a Data Engineer
Data engineers need to be tech-savvy, problem-solving experts who relish facing challenges and seeking optimal solutions. Check out Maryville University’s online Master of Science in Data Science to find out more about the data engineering opportunities that could await you.