How to Become a Data Engineer

Data engineers collect and store large quantities of data through software engineering methodologies, gleaning insights that can be used to determine organizational efficiency, and inform business-critical decisions. 

Once data is captured, data engineers use machine learning and statistical methods to observe any meaningful trends or patterns that could be used by their company. These trends inform how engineers develop new algorithms to capture and act upon new data. As such, data engineers can play an important role in helping organizations continually operate at optimal capacities.

There are a number of roles in the field of data science, including positions for big data engineers, database administrators, software developers, computer network architects, computer and information research scientists and more. Because of that, data engineer salary varies depending on the field.  

There are three main professional levels available to those seeking data engineer positions. As with other careers, each data engineer career level is based on years of experience and relevant skills. The levels are as follows:

Starting out as an entry-level data engineer doesn’t usually require any prior experience as this position is intended to introduce recent college graduates to a career in data engineering.

Entry-level data engineers may begin their career as an information technology assistant or database administrator. Such entry-level data engineer jobs enable them to get their feet wet programming actual data acquisition software, which will be used by members of their organization. In addition, they’ll be expected to start inserting data into databases. 

Through their daily work, entry-level data engineers will be introduced to many of the basic fundamentals of data engineering, gaining a peek into what their potential future as a junior- or senior-level professional might look like. 

Entry-level data engineer salary varies from role to role. Employers also consider factors such as education and volunteer experience when coming up with salary ranges.

Naturally, a junior data engineer has more experience than an entry-level data engineer. Depending on the position, becoming a junior data engineer may require a Bachelor of Science in Data Engineering or a related degree. 

Junior data engineers are typically responsible for integrating best practices related to data and data engineering by using previously established data pipelines. They develop data infrastructure to maintain strong data processing pipelines. Beyond that, they often perform entry-level data engineer responsibilities, such as programming software to be used with data structures or working hands-on with databases. 

Junior data engineer salary can change depending on the position, but personal qualifications and professional credentials may help candidates reach the higher end of the range for their desired role.

A senior data engineer professional typically has several years of experience making them an expert in the field.

Senior data engineers are responsible for building, testing, and documenting key data structures. They work on developing best practices for testing data pipelines to drive test coverage. They also work hands-on with databases, even more often than entry level and junior data engineers. They are proficient in technologies such as SQL, Data Factory, and the Microsoft Cloud stack.

Depending on the position and industry,  a senior data engineer salary may reach six figures. For example, the highest 10 percent of database administrators earned a median salary of more than $155,660 in 2020, according to the Bureau of Labor Statistics (BLS). Those working in data processing, hosting, and related services earned $108,520.

There is a wide variety of data engineer jobs available in today’s market. Students pursuing a data engineer job are knowledgeable in the primary areas of study required to land data engineering roles such as programming languages and methodologies, working with databases, big data engines, and data warehouses. 

Data engineer jobs include, but are not limited to, roles like:

Analytics engineers take data collected by a data engineer and attempt to make it compliant with modern engineering practices while also managing data pipelines using data tools. They possess both software engineering and data analytics skills, making analytics engineers something of a hybrid role by blending the responsibilities of data engineer and data analyst.

Individuals pursuing data analytics engineer jobs may benefit from studying computer science as it allows them to become adept at programming fundamentals. Studying data engineering technologies such as SQL, Scala and Python can also help individuals in this role.

Data analytics engineer salary averages range widely depending on the applicant’s level of experience, the position and more. 

Data center engineers work from data centers to manage who is allowed access to data within an organization. They’re responsible for maintenance tasks related to data center support, and they ensure that authenticated users can easily access needed information that is protected from unauthorized access. They may also assist with storing and organizing important operational data such as company records and financial documentation. 

Before applying to data center engineer jobs, it’s important for aspiring professionals to obtain skills relevant to computer science and information technology, such as hardware and software installation processes, cabling and hardware, and software troubleshooting. It’s also important to understand how to design and engineer automation systems such as industrial robotics. 

Typically requiring a bachelor’s degree, data center engineer jobs are available at the entry, junior, and senior levels, and data center engineer salary varies depending on these levels of experience.

Data visualization engineers take complex information and make it easily understandable through visuals. Using computer graphics tools such as Tableau and Illustrator as well as programming languages such as HTML, CSS and JavaScript, they help to identify important trends and insights in hopes of boosting an organization’s bottom line. 

People seeking data visualization engineer jobs usually study techniques for data visualization as well as visual design, software engineering and user research. They must understand how to design sophisticated data visualization systems throughout the entirety of the development process.

Data visualization engineer salary in the US will depend on a host of factors, including the number of years of experience an applicant has.

A big data software engineer uses large data processing systems as well as databases to interface with data at massive scales. These engineers use algorithms and analytical methods to comb through huge repositories and find problem-relevant data to analyze. Armed with this data, organizations can attempt to predict market behavior and make more strategic business decisions.

Applicants to big data software engineer jobs commonly hold at least a bachelor’s degree in computer science, data science, statistics or a related field. They will likely need to be proficient and knowledgeable in subject matters such as database architecture, statistical modeling, database querying languages such as SQL, and algorithms for predictive modeling.

The median annual salary for software data engineers in the US varies from industry to industry.

Obtaining a degree in data science can help students establish a strong foundation for a career as a data engineer. The UC Berkeley School of Information prepares data science professionals to innovate and lead in this field by merging a multidisciplinary curriculum, expert faculty hailing from top data-driven companies, an accomplished peer network, and the flexibility of online learning.

This WASC-accredited program can bring UC Berkeley’s premiere data science education to students wherever they are. Get started today.

Learn More About UC Berkeley’s Online Data Science Program