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35h per week
August 03, 2021
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October 05, 2021
Store, transform and transfer large volumes of data
Deploy Machine Learning models for production start-up
Create streaming data processing pipelines
Understand an organization’s storage and computing architecture needs
Build automatic data acquisition and processing pipelines
Deploy and adapt Machine Learning models on production servers.
Define a global Data strategy from acquisition to production, including storage and reprocessing.
More than 90% of our trainees find a job at the end of the training.
Are you still hesitating on the route to choose closest to your expectations?
A member of our DataScientest team will be happy to help you make the right choice.
The Data Engineer Job:
The role of the Data Engineer involves real engineering. It consists of developing tools to manage large volumes of data and make them accessible and usable by his team.
That data is then used by data scientists and analysts who will be responsible for making sense of them thanks to their business intelligence skills. In constant contact with customers as well as data scientists and analysts, the Data Engineer’s objective is to find the most appropriate solution to meet their needs. Want to know more about the job of data engineer?
According to a survey we conducted among fifty Chief Data Officers and managers from 30 CAC 40 companies (Allianz, AXA, BNP, etc.), the missions inherent to the Data Engineer’s job are (in a hierarchical order):
Creating data pipelines
Ensuring the maintenance of the Big Data architecture
Carrying out a technological watch on the transport and storage of data sets
Provide clean, quality data to Data Scientists
Coordinate the implementation of the Big Data architecture
Design and industrialize the models
To carry out these missions, the Data Engineer calls upon several skills including (in order of priority) :
- Object-oriented programming (Python R Scala)
- Big Data Tools
- Control of IT infrastructures and their performance
- Préparation des données
- Connaissances des principales architectures applicatives
- Compréhension des enjeux business
- Data Vizualisation
- Connaissances en algorithmiques – Machine Learning
To discover all the Data Engineer’s skills, click here !
To be eligible for our course, each learner must have the equivalent to a master’s level in science or Bachelor’s level in computer science with statistical notions.
Even if this job is centered on data, it requires good knowledge of mathematics and especially statistics, which will also enable you to grasp new notions during our training course more easily. It is also necessary for a data engineer to have a solid background in programming
To train as a data engineer, it is necessary to have certain prerequisites in mathematics such as statistics and linear algebra in order to analyze quantities of data and represent them in a matrix to facilitate their management. However, the essential notions to master are programming methods, algorithms and databases BDD.
We have developed a Data Engineer curriculum that is as close as possible to what is expected of a Data Engineer. At the end of your course, you will know how to:
- Query, manipulate, order and modify a data set with Python
- Understand the basics of object-oriented programming – OOP
- Understand the architecture of an operating system (such as Linux)
- Master and customize a wide variety of fundamental graphical renderings for Data Vizualization
- Implement a classic Machine Learning algorithm
- Select and optimize a Machine Learning algorithm
- Optimally reduce the size of a dataset without loss of information
- Understand the specificities of distributed architectures
- Read and query relational databases
- Understand the interest of API development
Once you have registered on the site, our teams will contact you to present DataScientest, our offers and discuss your journey. The idea is to confirm that the training you want to follow is in line with your expectations.
Following this, a technical test of mathematics (probabilities/statistics and algebra) is submitted to you to position you. It is used to define your level at the beginning of the training.
Our admissions team will then communicate the results to you and will not hesitate to contact you to discuss your motivations and the good foundation of your project.
You are in no way committed to DataScientest and you can decide at any time to stop your project if you wish.
It is only once the project has been confirmed that your registration phase begins. During this phase, our teams will take care of initiating your Data Engineering training as well as discussing with you all aspects of your professional project.
DataScientest is the only organization to offer hybrid training, i.e. both face-to-face and distance learning. (approximately 15% and 85% respectively). This makes it possible to combine flexibility and rigor without compromising on either one or the other. It is a well thought-out choice that motivates our pedagogy so that learning can be carried out to its conclusion with motivation. We have in fact detailed the advantages of this unique combination in an article on the subject.
Moreover, it is also possible to follow distance learning: face-to-face courses are then replaced by videoconference courses. However, the follow-up remains the same: the teachers remain attentive and follow you throughout your course.
Several blocks make up the training. Each block is divided into several modules.
For the Data Engineer training, the blocks are :
- Data Visualisation- Dataviz
- Machine Learning
- Big Data and Dev Ops
More details are available in the attached syllabus The total duration of a course is 325 hours, in bootcamp (11 weeks) or continuous (9 months) format.
Of course! And who better to provide support than our teachers, who also designed the program. They are available and ready to listen to all questions, whether theoretical or practical, and will be able to demonstrate pedagogy in their answers.
In addition, to ensure the completion and commitment of each student, our teachers follow your progress closely. As soon as you stop logging in for an extended period of time, your cohort leader will check in on you: we won’t let you down!
Finally, our papers, exams and papers are also corrected by hand by our panel of qualified teachers: everything is done so that everyone can progress at his or her own pace in an efficient manner. At DataScientest we are convinced that only a personalized follow-up ensures quality learning!
According to the Data managers of the major CAC 40 companies, for a Data Engineer, communication, both oral and written, is more important than the company’s business know-how.
That’s why we have adapted our curriculum, which now emphasizes these soft skills with :
- Written and oral support for the project
- Data class around project management or management tools that are now part of the syllabus
- Masterclasses on “best practice in data visualization” that complement the curriculum.
- For those who wish, the possibility to participate in CV workshops and career coaching via the career managers and the HR team of DataScientest.
As part of our partnership with Panthéon Sorbonne, each of our Data Scientist, Data Analyst and Data Engineer training courses is now recognized by La Sorbonne. You can now benefit from the recognition of a world-class university. These certifications are a pledge of quality that guarantees a complete content adapted to each of our learners.
In addition, as a B2B leader in data science training, DataScientest is well known among companies that entrust it with the data science training of their teams. This trust has forged the recognition of its diplomas.
Finally, the data engineer diploma is currently being validated by the RNCP to the level of a level 7 diploma (Bac +5) and should be validated in the coming weeks.
The Data Engineer career:
Training in data science means opening up new fields of opportunity! A large part of quantitative professions (researcher, actuary…) that rely on statistics require a mastery of data. This last one allows then to access new opportunities.
To follow a Data Science Professionalization is to open new horizons!
After training, the Data Engineer can also take a training course to become a Data Scientist, which is also available on DataScientest.com. To discover it, click here!
Then, after a few years of experience, he will have the opportunity to evolve to the position of IT Director.
To answer this question, we conducted our own survey of some 40 partner companies.
To discover the details of the survey, as well as the remuneration of data science professions, read this article!
The salary of a Junior Data Engineer varies between 45 and 50,000€ per year. Once promoted to Senior, his or her salary will rise to €50,000 or even more than €60,000 per year.
These figures are based on our survey of Chief Data Officers of CAC 40 companies, details of which are available on this link.
According to the survey conducted among all our Data Engineer students, 93% of them found a job immediately after completing their training.
Our post-training support services
Beta-tests are made available to our alumni in order to gain data knowledge even after the end of the training.
Our Data Scientists design newsletters that will be sent to you on a regular basis to keep you up to date with Data news. To receive the next one, click here !
DataScientest alumni are more and more numerous.
To bring them together, DataScientest has launched a LinkedIn group for all its alumni in order to keep this link alive and to ensure contact between alumni.
They will then be able to exchange on various Data Sciences related topics. Beta-tests are made available to our alumni in order to gain data knowledge even after the end of the training.
The DatAlumni community is a LinkedIn community that gathers DataScientest alumni. On this page, questions, tips and new technologies are shared for the benefit of all.
To discover all the benefits of this community, read this article!
On top of that, DataScientest will launch in the coming weeks a thrombinoscope that will allow to connect alumni, it will include the company and the position of each one.
Initially, DataScientest supported the data transition of companies.
This allowed us to create strong links between the major groups that ensured the growth of our structure.
Subsequently, they were the ones who motivated the launch of our offer to individuals in order to compensate for the lack of competent profiles.
This need for good profiles is reflected in the survey we conducted among some 50 Chief Data Officers and managers from 30 CAC 40 companies.
Even with high budget constraints, only 4% believe they would reduce their data scientist workforce: compared with 28% who would still seek to increase their numbers by more than 20%…
On the strength of our history with large companies, we have signed partnerships linked to the hiring of our alumni. All our partner companies are committed to integrating all our students at the end of their training into their processes: this, coupled with assistance with CVs and interviews, means that you will be in pole position to land the job of your dreams!
Not only can we help you, but we are also in an ideal position to do so and enable you to succeed in your professional integration.
During your training, monthly career workshops are organized to help you write a good data oriented CV and to train you in data science recruitment tests. You can also benefit from the personalized advice of our career team.
Depending on the sector you wish to work in, our team will be able to advise and guide you thanks to its collaboration with many companies.
To discover the list of our partner companies, click here
To find out more about DataScientest’s career support actions, click on this link