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How to Become a Data Visualization Engineer

By now, it is more apparent than ever that our entire world runs on data in some form or another. Data visualization engineers have therefore become an important cog in the technological wheel.

Whether through artificial intelligence, machine learning, or analytics reporting, we have never had a better, more detailed view of our world. Using data analysis, data visualization engineers can inform companies to launch advertising campaigns, sell an item, or even play it safe in the marketplace.

After all, data paints a telling picture. But how do you break into the field of data visualization? Let’s take a closer look.

What Is a Data Visualization Engineer?

A data visualization engineer is someone who takes exceptionally complex data and turns it into something everyone can understand through the use of data visualization tools. Data visualization engineers use the field of descriptive statistics to both figuratively and literally create a picture of what data represents from a particular collection.

What Does a Data Visualization Engineer Do?

A data visualization engineer is responsible for data. By using everything from data analysis to graphic design, data visualization engineers translate data making it more useful for others. Let’s take a look at a few of the key responsibilities of a data visualization engineer.

Makes Complex Data Not So Complicated

Above all, talented data visualization engineers translate numbers, trends, and more into understandable mediums. For example, a company may want to know how well a specific item sells during the month of November over the past decade.

What would be the best way to exhibit this? A line graph? A bar graph? Data visualization engineers need to explore the existing data and choose the best way to communicate findings with others.

Develops Data Visualization Tools

While there are some helpful data tools out there (it never hurts to learn Stata and other statistical programs), some big data experts may not be satisfied with the current data tool kit.

There is always room to improve individual programs and tools, and finding unique mixes and matches of preferred methods of analytics reporting and data visualization depends on the user. Keeping in tune with likely future trends, you need to have the most current software and techniques to ensure success in your endeavors.

Spot Potential Future Trends

Having your ear to the ground (and your eye on the charts) is a beneficial tool to have. Data visualization engineers can harness their knowledge to even predict future trends.

While it’s impossible to entirely predict the future, data visualization engineers have certain ‘secret superpowers’ to help them get somewhat of a better idea of what the future holds.

By learning predictive analysis, data scientists and those working with data can help make critical business decisions for individuals and corporations. Predictive analysis can help find relationships between variables, help with credit scoring, and more.

Essential Data Visualization Engineer Skills

If you are already good with numbers or think like a data scientist, then you may already have a leg up when it comes to having the skillset of a data visualization engineer. Let’s take a look at what you need.

An Eye for Detail

It may be obvious, but to effectively visualize data trends, you will need to have a good eye for detail. It only makes sense, as clients, big companies, and more may all make decisions based solely on the analysis provided by you.

Good With Numbers and Data

Data visualization engineering will come easier to those already entrenched in data science.

It’s by no means impossible for someone who isn’t familiar with data science to analyze charts and trends. However, having a strong foundation in data analysis and computer science makes things considerably more manageable.

It also helps if you are proficient at math, programming languages, and especially statistics.

Knowledge of Programming Languages

Learning to code may be one of the most essential parts of data science, other than the data itself. Learning any programming language can help you excel in the job marketplace. However, arguably the most useful skill to have in data analysis and data visualization is SQL.

If you want to reap the most valuable benefits from data collection and data analysis, learning SQL is strongly recommended. The ‘Structured Query Language’ helps data engineers work closely and more efficiently with complex databases.

Overall, it’s always useful to know a little about any programming language if you want a career in data science or data analysis. Plus, it will definitely help your career prospects if you have SQL skills on your resume.

Data Visualization Engineer Salary

Now that you have a better understanding of what a data visualization engineer does, how do these responsibilities benefit you in the real world? Let’s take a closer look at the salary of a data visualization engineer.

You have an extremely high potential for significant earnings. According to PayScale, an average data visualization engineer salary can clock in at around $98,264. And that is only the average.

Senior data visualization engineers and data scientists can earn well over $140,000 annually. Sure, these salaries usually tend to be for project managers and senior data scientists, but even the lowest 10 percent of salaries are extremely impressive.

Overall, the scale of the salary of a data visualization engineer ranges from $86K to $140K. Even the most amateur data analytics expert can make an impressive living parsing out complex data.

Job Outlook for Data Visualization Engineers

Data visualization engineers have it made. The considerably high salary coupled with job security suggests there are promising career opportunities for anyone interested in visualizing data. According to the Bureau of Labor Statistics, all data-related fields will grow by around 15 percent over the next decade.

In short, there will always be a need for complex data to be broken down into simpler, more digestible terms. This means that there will almost always be a place for talented data visualization engineers.

How Long Does It Take to Become a Data Visualization Engineer?

It takes at least four years to become a data visualization engineer. If you want to make data visualization your livelihood, you will need at least a bachelor’s degree from a university. For some companies, applicants will sometimes also require a master’s degree. This could inflate your schooling time to around six years.

The length of study will depend on where you are applying for a job and what your specific duties will include. For example, some government departments will hire an engineer with only a bachelor’s degree, however, if you want to be a project manager and seek out senior data positions, you may want to pursue your master’s degree right away.

How to Become a Data Visualization Engineer: Step by Step

Now that you know all about the key responsibilities of a data visualization engineer let’s examine the steps necessary to succeed.

Step 1: Obtain a Bachelor’s Degree

The only surefire way to get a job in any data-related field is by attending colleges and universities. While you may be able to skate by with an associate degree in computer science for some data-related jobs, the truly lucrative data visualization engineer positions need more credentials.

Majoring in something like computer science, statistics, or any other data or number-related field can net you success on the road to employment.

Step 2: Consider an Internship

Although it is enticing to shoot straight for that cushy job you have been working so hard for, you will need work experience. One of the tried and tested methods of gaining first-hand work experience is through data-related internships.

Sure, you may have to get the team coffee sometimes, but the actual work experience, combined with the inclusion of impressive credentials on your resume, may give you a great advantage.

Many companies offer great internship options, both paid and unpaid. Look around for an internship that fits your career goals and interests.

Step 3: Pad Up Your Portfolio with Projects

While the straight path from college to employment may seem a bit obvious, there are a few ways to ensure that you get hired.

There are various data visualization projects that you can engage in. These are essentially problems and data sets that put your skills to the test. Since there is a staggeringly large amount of data worldwide, finding these ideas to execute isn’t that hard.

Step 4: Go for that Data Visualization Engineer Job

Now is the time to combine both your schooling credentials and real-world work experience to nail your job interview. Update your resume, include a portfolio of all your data visualization projects, your internship experience, and start applying for jobs.

Should You Become a Data Visualization Engineer?

If you are at all familiar with data science, data analysis, or any facet of computer science, you should absolutely consider a career as a data visualization engineer. Data visualization is so much more than just plugging numbers into a program like Stata and making conjectures.

Data visualization engineers need a keen eye for detail, an intuition for great graphic design, and effective communication methods with clients, superiors, and fellow team members. Learning data visualization may not be straightforward for some, but it can be gratifying.

The job security and salary are both fantastic, and you can get there with a four-year degree. If you are willing to put in some hard work and commit to learning computer science, programming languages, and analytics, becoming a data visualization engineer could be perfect for you.


What degrees do I need to become a data visualization engineer?
Graphic design, data science, computer science, and others. While there is no definitive major for data visualization and its many subsets, earning a degree in any of the above majors can help you on your way towards a career in data visualization.
What are the best data visualization tools?
Some of the best data visualization tools available are: 1. Tableau 2. Zoho Analytics 3. Qlik Sense 4. Microsoft Power BI 5. Klipfolio 6. SAP Analytics Cloud 7. IBM Cognos Analytics 8. Sisense 9. Looker
What is the difference between data visualization and data science?
While both disciplines deal with data, data visualization is a substantial part of descriptive statistics. Data visualization engineers use graphic design skills, statistics knowledge, and more to execute their responsibilities and report on data. Data science is the more significant, more general field responsible for data collection, study, and analysis.
What are some data visualization techniques?
There are numerous ways to take data and visualize it. Some of the best methods of visualizing data are: 1. Histograms 2. Box plotting 3. Various Charts 4. Tree Mapping 5. Graphing 6. Heat mapping
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