Data scientist, data engineer, or data analyst: what is the difference?
In a world that runs on data and insights, it comes as no surprise that IT jobs also increasingly require skills to work with data. Profiles such as data scientist, data engineer, and data analyst, are therefore commonplace on every IT job site. But what is the difference? And what do you need to start working in one of these domains?
The demand for data-related skills has been growing for years. According to the US Bureau of Labor Statistics, the number of jobs requiring data skills will increase with another 27.9% by 2026.
While the mountain of data grows every day, the number of data-skilled profiles on the job market is still rather limited. Organizations struggle to attract the right people, and making up for this shortage by reskilling existing employees is not obvious. Data science requires basic knowledge of statistics. As a result, organizations often pay attractive salaries to convince someone with the right background.
Never say data scientist to a data analyst or data engineer. Although these three profiles are working in the same domain, we need to distinguish their skills and tasks.
1. Data analyst
The role of data analyst is a good starting point if you want to dive into the world of data science. Your main task is translating numeric data into information that everyone in the company understands. For this, you need to process data, apply general algorithms and summarize results in reports.
A good understanding of statistics is the biggest requirement to pursue a career as a data scientist. Of course, technical skills are a plus and give you an edge over other candidates. You should therefore have a basic knowledge of a programming language such as Python, be able to work with tools such as Excel, and understand the key principles of data processing and reporting.
As soon as you have enough experience as a data analyst, you can grow into the role of a data engineer and eventually even a data scientist.
2. Data engineer
The role of data engineer forms a bridge between a data analyst and a data scientist. You certainly need more experience and technical knowledge than the average analyst. As a data engineer, you are responsible for connecting and preparing data for operational or analytical purposes. You must be able to extract insights from Big Data and draw up reports that data scientists in your team can analyze.
As the name and function suggest, a data engineer also needs skills to build, develop and maintain data architecture. For example, by setting up large data warehouses and merging data from various sources.
In a next step, a data engineer could consider a career as a data scientist as well. Although that requires a hefty learning curve with a bunch of new and more in-depth skills.
3. Data scientist
The most specialized (and therefore best-paid) role in the data universe is that of a data scientist. From preparing unstructured data and analyzing Big Data, to building models and generating results that have an impact on the company’s performance. These are just a few tasks that allow data scientists to make a difference for their employer. As a data scientist, you need extensive knowledge of statistics, machine learning, and techniques for managing and processing data.
Data scientists typically have a senior role and can fall back on their experience. They use input from data analysts and data engineers to generate important business insights and solve complex problems. Fortunately, today they can count on the contribution of AI to take over some of their work or move it to another role in the company. This enables them to focus on the work that really matters: performing complex analyses and identifying new opportunities for the business.
Engine of the company
Conclusion? As everything is constantly changing, companies need insights from data to innovate and stay on track. As data specialist, you are a key component of the engine that drives the organization. Apart from a healthy passion for data, we can say that data scientists, data engineers and data analysts have something else in common… They all have a job that will be critical to the future of our companies, and even our entire society.
Do you fancy a job as data analyst, data engineer or data scientist? Or do you have another IT super power? Then take a look at our vacancies!