What is a data engineer? What are their technical skills? How do you train for the job? What is a data engineer's salary ? Answers below.
Driven by the need to handle ever-increasing data flows, the job of data engineer is becoming increasingly attractive. The data engineer is now an indispensable pillar in ensuring the proper use of data.
In addition to solid job prospects, data engineers can expect competitive salaries from their early years. While data engineers must demonstrate programming knowledge, rigour, analytical skills and good communication skills are also essential. In this article, we summarise what the job of data engineer is and the salary potential of the function.
What is a data engineer ?
A data engineer is responsible for selecting, sorting and organising data flows from different sources. He or she focuses on the arrangement of the data while ensuring the scalability of the system and its security. He therefore organises information and creates data pipelines so that data scientists or other customers (usually internal to the company) can use it.
A data engineer can be compared to an architect who draws the foundations and plans for a building or a plumber who organizes the piping for a house.
The adage is known in the industry: « Garbage in, garbage out ». In other words, lead is not transformed into gold. Based on a data processing system, the data engineer's work can therefore have a large-scale impact on the entire company.
Moreover, with the rise of artificial intelligence and machine learning, the role of the data engineer is changing dramatically. We will come back to this in the rest of this article.
Is there a shortage of data engineers ?
If the term shortage may seem exaggerated, there is in any case a strong demand for data engineers.
The evolution of technology implies ever more sophisticated data processing. If today data engineers mainly use distributed computing solutions to organise their data, they must already rely on artificial intelligence and the learning machine as an aid in data processing.
This market is expected to reach $1.2 billion by 2023.
The profile of the data engineer is therefore becoming more complex because if these models are not properly trained, the whole system is compromised. This brings us back to the famous adage « Garbage in, garbage out ».
According to the Dice Tech Job report 2020 (jobs in the technology sector on the American market), the function of data engineer is the one for which demand is currently growing fastest (50% over one year). LinkedIn estimates this growth at 33%. In both cases, the demand for the data engineer profile is clearly increasing.
How do you train as a data engineer ?
Data engineers have a variety of backgrounds.
In general, a Bac+5 degree is required. Typical profiles include computer science graduates, computer engineers, statisticians (with a focus on IT) or data specialists. However, the profiles in the field are very diverse. This is due to the fact that the position is still relatively new and continues to evolve.
At present, many internationally recognised companies offer data engineering certifications. This is the case with Google and IBM, for example.
What are the technical skills of the data engineer ?
Generally speaking, the data engineer is familiar with the Big Data environment and the tools that make it up. They must also be able to master ETL processes and keep up to date on the subject. The main requirements are as follows:
- Python, Java, Scala;
- ETL (Extract-Transfrom-Load);
- Good understanding of SQL and NoSQL databases;
- Apache Spark, Hadoop, AWS.
Python has gained essential status in recent years due to its applications in machine learning. Similarly, mastery of Amazon Web Services (AWS) has become a priority. On the other hand, languages such as Java and Scala, which were an integral part of the Hadoop era, are tending to lose importance.
Nevertheless, a good data engineer will be familiar with all the tools at his disposal and will know how to use them wisely to achieve his goals.
What are the essential soft skills of the data engineer ?
- Communication: the data engineer is at the service of the company. Their direct clients are generally data scientists. Data can be organised and arranged in millions of different ways. The data engineer must therefore understand and grasp the objectives pursued in order to develop an optimal architecture;
- Analytical mind: the data engineer must be able to visualise data flows in order to order them to achieve a goal. This implies the ability to take a step back;
- Rigour: if the data engineer is careless or lacks rigour in his analysis and choices, the entire data processing system may be compromised.
What salary does a data engineer receive ?
Good data engineers are entitled to high salaries. Demand is high and complete profiles are rare.
According to the Kicklox platform, a junior data engineer in France can expect around 3,700 euros gross per month. Some less optimistic sources put the starting salary at between 2,500 and 3,000 euros per month.
There is a lot of room for growth and the salary package can therefore increase rapidly.
In the United States, the average annual salary for a data engineer with any experience is around $130,000 according to Indeed.com. Recruitment firm Robert Half estimates the median salary at $163,250 in its Salary Guide 2020.
Let's recap !
- The primary responsibility of the data engineer is to create a global infrastructure to collect, process and organize data;
- The demand for data engineers has been increasing sharply for several years. The profession is evolving to take account of technological advances in the fields of AI and machine learning;
- In 2020, a data engineer must master the following skills: Python, ETL, Big Data, AWS, SQL. They must also be rigorous and analytical;
- The average salary of a data engineer starting out in France is around 3,000 euros per month. The salary can increase rapidly and is much higher in the United States (around $100,000 a year for a junior).
The on-demand data processing software developed by Ryax responds perfectly to the evolution of the data engineer's profession. By automating part of the work, the Ryax platform allows data engineers to focus on the global architecture of data flows and to arrange and process the different data sources in an optimal way.
The Ryax Team.