Data For Dummies; Data Jobs Explained

In the last couple years a lot of new jobs are created or get more popular and valuable within companies. These Data Jobs evolved from developments in the technology era we live in. Data is becoming the most valuable asset and handling this asset increases in complexity every day. The cost of storing or processing data is no longer a cost-driver and a boundry for companies. Collecting and using data for in order to sell advertisements are business models for many companies these days. Look at the well-known companies like Google and Facebook or at the data brokers like Acxiom and Experian, they sell added value based on data collection.

Data Jobs

With this new “gold” all new kind of data jobs are rising. From the outside all these jobs come with a certain complexity and overlay between them. What do we mean we when we say “data analyst” and what is the difference with the “data scientist”. Just ask around and you will find out that most people do not know the difference. Therefore I will give you a brief explanation about these jobs. I selected the five most common listed data jobs. I will try to compare these jobs with “familiar” equals we all know from our daily lives.

The “Data Architect”

In technical terms a data architect should be able to set standards for all data systems within and outside a company IT landscape. The vision and model about interactions between all these systems should come from the point of view of the architect.  The translation finds its way into a “normal” architect for example of your house. The architect fits all the needs of you and your partner into a house and makes sure that everything is connected for its purpose. The toilet is often in your hallway, the dining room is next to your kitchen and the closets are fitted into the bedrooms. The house is designed as a combination of your wishes and practical use. Logical combinations with a higher purpose of satisfying the needs of a person/company can be described as the main goal of the architect.

The “Data Engineer”

You can compare the data engineers with plumbers. They maintain and build the pipelines for this amazing kitchen or bathroom. Data engineers clean, prepare and optimize data from different sources for consumption by the next data expert in line. As a data engineer you have an important supporting role because you are the one who helps build the underlying infrastructure. “You can have an amazing kitchen, but if there is no water, what is the point?

The “Data Analyst”

The main tasks of data analysts are to collect, manipulate and analyze data. They prepare reports, which may be in the form of visualizations such as graphs, charts and dashboards, detailing the significant results they deduced. Data analysts guard and protect the organization’s data, making sure that the data repositories produce consistent, reusable data.

This description makes it not easy to translate it to normal language. However if we try, the first thing that comes in mind is an Accountant. The accountant does the same for companies on mainly financial data. The main difference is that the accountant can be seen as the conscience from outside the company to prevent abuse.

The “Master Data Steward”

It might be a little strange to have this specialist in line with the others. Mainly because of the fact that this kind of data is the “oldest” in the room. Master Data is the data that every company possesses even far before the internet time. Usually defined as Products, Vendors, Clients and Assets. This specialist makes sure that the foundation of the companies data is correct and stays correct. I would like to compare this one with a guard of the vault at your local bank. This person oversees all that goes into the vault and comes out. What is in there does not matter, as long as its compliant with the rules of the bank.

The “Data Scientist”

The data scientist possesses a combination of analytic, machine learning, data mining and statistical skills as well as experience with algorithms and coding. A real “mathematical” wizard with data however the most important skill is the ability to explain the significance of data in a way that can be easily understood by others. For this role there is no equal. The one that comes closest in my point of view is the “professor” at the University whom student love most. The capability to translate complex matters into an easy story that can be understood by everybody.

I hope that a lot of readers now get some clearance about all these different types of data jobs. This is just a tip of the iceberg and many more roles are we defining right now. The main conclusion is that we are in the “data era” and many more is coming.

I would like to address a special thanks to sources like Google, Wikipedia, LinkedIn,, and many other I am probably forgetting right now. .