Data engineering has been a top trending job for some time. In 2019, companies continue to seek out professionals for data engineering positions. According to one study, there was an 88.3 percent increase in the number of job postings featuring the phrase “data engineer” over a 12-month period. As a result, data engineer is considered the top trending job so far this year.
If you are wondering why data engineering remained in the top spot, here’s what you need to know.
As big data made waves in the business world, a range of new job titles emerged that described some of the critical functions associated with harnessing the power of a company’s data. But, with many of them being similar, it can be hard to identify the differences between the roles based on their job titles alone.
The data scientist and data engineer titles are a prime example, as they may seem similar on the surface. However, these are unique professions, and which you choose with impact how your career develops.
If you aren’t sure whether a data scientist or data engineer career path is right for you, here’s what you need to know.
A data scientist is a professional who can take raw data and turn it into something meaningful. Often, an understanding of statistics, analytics, and machine learning are required, enabling these specialists to solve a variety of critical business problems or answer important questions.
At their core, data scientists take large quantities of data and use the information to generate actionable insights. This requires strong programming skills, an understanding of algorithm creation, data visualization skills, and high-level problem-solving skills.
Some of the commonly requested hard skills include Apache Spark, Hadoop, Python, R, deep learning, machine learning, and statistics.
A data engineer is usually responsible for handling the infrastructure that supports the big data activities of data scientists. Often, this includes designing systems, building solutions, and creating mechanisms that allow information from a variety of sources to integrate.
They may also compose complex queries, ensuring that the data is accessible and the larger system operates efficiently, and design data warehouses.
The ultimate goal of most data engineers is to ensure that the proper system design and architecture are in place, and usually aren’t expected to have high-level skills in areas like analytics and machine learning.
However, commonly requested skills include Hadoop, MapReduce, SQL, NoSQL, MySQL, and Cassandra.
Which is Right for You?
Ultimately, which career path is right for you depends on your skill set and personal preferences. Both options can lead to a lucrative and long-lasting career, particularly since companies are likely to continue pursuing data-oriented objectives for years to come.
Both roles are important in the data landscape, so one isn’t inherently more valuable than the other. Without data engineers, data scientists wouldn’t have the infrastructure they need to get their jobs done.
There are also other roles associated with big data that may be appealing, such as data analyst positions, so you aren’t restricted to only exploring data scientist or data engineer job.
If you are interested in finding a new opportunity in any of the above career paths, the professionals at The Armada Group can help you explore your options and connect you with leading companies throughout the area. Contact us today to learn more about how our services can benefit you.