Creating thousands of jobs around the world, big data has become companies’ lifeblood! Among the most sought-after jobs, Data engineers have their own time at the podium. We conducted an investigation to find out everything about this profession, from salaries to role, missions, skills, and more.
The data market: a promising and rapidly expanding field
As the amount of data created and used grows exponentially, the complexity of collecting, sorting, and analyzing it increases. This is why companies are focusing on candidates with specific backgrounds like data analysts, data scientists, and data engineers to be able to make strategic, data-driven decisions.
We’ve observed a twofold trend:
- A real shortage of experts: according to QuantHub, 85 million data specialists will be needed in the market by 2030. That's a lot of tech talent to find!
- A growing demand from companies looking for recruits in big data, and therefore a jump in the number of this sector’s job offers.
What is big data?
The term big data is used to define a large complex data set from heterogeneous and new sources. Defined by three "V's"—volume, velocity, and variety—it includes varied data that arrives in large and growing volumes at a high speed. Today, so much data is produced that traditional data processing software can’t handle it.
Big data is present in countless other fields, including science, marketing, education, environment, health, and others...
What’s the purpose of big data?
Big data’s main goal is to allow companies to take advantage of new data that’s produced every day. It’s the result of both new needs and new businesses.
What jobs does big data offer?
Big data offers a variety of positions, including:
- Business intelligence analyst
- Chief data officer
- Data analyst
- Data architect
- Data engineer
- Data miner
- Data protection officer
- Data scientist
Today, we’re focusing on just one in particular: that of the Data engineer.
What’s a Data engineer?
And what role does a Data engineer play?
One mission Data engineers have is to build the architecture of the big data system—in particular, what’s called the ETL* pipelines. His role is to ensure the collection, manipulation, transformation, and storage of data from different sources. The main challenges they face here are:
- management of large volumes of data
To make this possible, they will develop tools that allow to:
- process large volumes of data
- make them accessible and usable for the whole team
Simply put, Data engineers embody a central role among the data professions, since they prepare the ground for data science and data analysis:
- Data scientists can use "clean" data and exploit it in a more complex way, draw trends, and infer with machine-learning algorithms.
- Data analysts can make better sense of large volumes of data thanks to their business intelligence skills.
Thus, Data engineers are not only in direct collaboration with the other data professions, but also with the customers to find the most suitable solution to meet their needs.
➡️ To explore further, check out our article: Data Analyst vs. Data Scientist : What’s the Difference?
*What is an ETL (extract, transform, and load) pipeline?
An ETL pipeline is a set of processes that include:
- extracting data from various and heterogeneous sources
- transformation of raw data to data that various apps can use
loading data that has a usable format into a data warehouse for analysis
ETL pipelines are used to make fast yet informed decisions.
Why become a Data engineer?
What trends are there for data engineering and the big-data professions?
As we’ve seen above, Data engineers are one of the leading professions in big data.
Data engineers often start out their careers in various other environments:
If you come from a rather data-oriented environment, training in data engineering allows you to specialize in big data through roles of...
- Guarantor of the production line
- Data architect
... while exploring the world of IT and development!
If you come from a rather developer-oriented environment, you can see that the big data professions are becoming more open and accessible to candidates with an IT background. Indeed, more and more companies are recruiting candidates with dual IT development and data backgrounds, which are not only key skills but also very popular ones as they allow for:
- Greater ease in communicating with other departments in a company
- More simplicity in the structuring and restitution of data so the company’s various actors can use it
For example, a good Back-end developer can become a Data engineer, because we find the same technologies that developers use in back-end development.
If you come from a sales/marketing-oriented environment, training in data engineering allows you to specialize in the job of a Growth engineer. Although essential within a growth team, this job remains relatively less known about. Simply put, Growth engineers have cross-functional roles. Depending on their specialization (business or marketing), they:
- provide support to the growth team
- collect data
- set up automations
- create MVPs (Minimum Viable Product: a first version of a new product that shares the essential features for its market launch)
- accelerate the Growth team’s actions and experiments
Data engineer: salary/benefits
How much do data engineers typically make?
According to the Clementine Jobs platform:
- A junior data engineer can earn about €45, 000 per year.
- A senior data engineer would earn around €60,000 per year.
The difference between these figures can obviously vary depending on...
- The company’s domain and organization
The Data engineer’s seniority and responsibilities (with a team to manage or not, for example)
If this article has made you consider becoming a Data engineer, there are programs such as the data engineer training program (in French) from Wild Code School that will allow you to acquire the necessary skills to practice this profession at the end of your course.
What skills do I need to become a Data engineer?
To be a successful Data engineer, you’ll need to know how to:
Develop a data ingestion and storage pipeline
- master the tools of the Hadoop ecosystem
- understand the challenges of big data
- understand the big data architecture needs of a company or organization
Process and analyze large volumes of data
- design, develop, and deploy automatic data processing pipelines
- prepare and load data streams to data warehouses and analytical tools
- build and model relational and non-relational databases
- using Apache Spark to process big-data workloads
Integrate and deploy an application
- deploying an application as a REST API
- provide a graphical user interface
What training is available to become a Data engineer?
To become a data engineer, there’s no need to train for years and years or obtain a master's degree first!
Today, short courses allow students to acquire a solid foundation with the experience and skills they’ll need for a demanding job market.
Wild Code School seeks to make the data professions accessible to all by expanding its training with a one-year work-study program in data engineering (only available in French). Many large companies, SMEs, and start-ups have already recruited data specialists who studied in our programs: Dataiku, Malt, Auchan, Decathlon, Keyrus, Betclic, Dailymotion, Teester, Criteo and many more!
"We believe strongly in the importance of continuous professional training. The ability to acquire new skills is fundamental in the world of work that we know, especially with the increasing diffusion of AI and the professions related to the development of data. Actors such as Wild Code School are essential in order to allow (young) workers to be quickly trained in these new professions, and it thus seems important to us to join them in addition to our partnerships with the more traditional actors of higher education," says Gildas Fresneau, Senior Academic Program Specialist at Dataiku, during an interview Wild Code School conducted in September 2021.
I’m a beginner. Can I still become a Data engineer?
Yes! One of our initial five-month training course in web development or data analysis will lead you to the main knowledge to have when you want to start a career in Data engineering:
- skills in mathematics, statistics, and algorithms
Are there any prerequisites to join one of these two courses? There are no prerequisites! You just need to be highly motivated and have a creative mindset to find solutions, a desire to succeed, and the ability to work on a team.
Apply now for...
I already have a background in web development and/or data. Can I become a Data engineer?
Of course! After a training in web development and/or data analysis, you have all the necessary skills to begin to train as a Data engineer!
Our French data-engineer training is open to two types of audiences (only French speakers):
- Students or trainees from professional training who have completed a course in web development or data analysis and wish to continue their training;
- Professionals who don’t necessarily have an advanced degree but who already have experience in web development or data analysis, or who have completed a training course of at least five months’ equivalent or similar to the web developer or data analyst training course at Wild Code School.
The goal is to allow anyone with significant experience in web development or data analysis to specialize in data engineering and launch their own career in big data.
Upon completion of this professional training, you’ll be able to:
- collect and store data (automation, data lakes, cloud services)
- prepare and process data (ETL process, transforming data using MapReduce, Spark)
- analyze big data with a cloud service like AWS RedShift
- provide a data warehouse
- view data
In short, if you’re still hesitating to retrain or specialize in the data industry, wait no more. It's a booming sector that guarantees a quick return in terms of work.
What if you were our next tech talent? All bets are in!
For more information on data, go to our "big data" category or read about our Wilders' journeys in the dedicated articles.