The Data Engineer Master’s degree
Know how to adapt to the digital transition of the 21st century and meet the economic challenges of digital transformation
- Duration : 2 years
- Intake: September
- ECTS credits : 120
- Language of instruction: French
- Pace: Work-study
Data Engineer level 7(EU)* professional certification, NSF code 326 issued by DataScientest, registered under number 38919 in the RNCP (Répertoire National des Certifications Professionnelles) by decision of the Director General of France Compétences on April 26, 2024.
*Only on a work-study format
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Master Data Engineer presentation
Data and Artificial Intelligence today represent major strategic challenges for companies and organizations of all types, sizes and sectors. Considered as essential tools for the digital transformation of companies, these disciplines create significant added value; data and AI professions, which create knowledge from large volumes of data, have now become indispensable to the digital transformation of companies.
The Data Engineer Master’s program trains future Experts and Managers in the issues involved in creating value from data management and artificial intelligence. Thanks to their managerial and technical skills, this program enables its graduates to master data analysis in order to gather the information needed to make strategic and marketing decisions and create innovative services. They will be ready to anticipate the different scenarios and possible uses of Data and Artificial Intelligence to meet the economic challenges of digital transformation.
Objectives of the Master Data Engineer
Design a technical architecture project for data management
Develop a technical architecture for data management
Manage a data management technical architecture project
Deploy a massive data analysis solution integrating artificial intelligence
Applications from French students or international students living in France
Applications from international students living outside of France
Skills targeted by this specialization
The Data Engineer is in charge of the design and development of infrastructures and tools dedicated to processing massive volumes of data, facilitating in particular the deployment of Artificial Intelligence solutions. The central mission is to orchestrate the collection of data and ensure its availability within the organization, thus creating an essential link in the data value chain.
- Competency block 1: Design a technical data management architecture project
- Identify data management architecture requirements
- Develop and implement a technological and regulatory watch system
- Use intelligence within your organization
- Define the scope of a data management project
- Make recommendations to line managers and members of a multidisciplinary team
- Competency block 2: Design a technical architecture for data management
- Collect structured and unstructured data from a variety of usable sources
- Develop storage solutions
- Design procedures for extracting, processing and storing architectural data
- Transform data into a format suitable for analysis
- Analyze data
- Automate data collection, processing and storage circuits
- Develop an artificial intelligence algorithm
- Competency block 3: Deploy a massive data analysis solution integrating artificial intelligence
- Design a programming interface between solution components
- Containerize architecture components
- Deploy the model in a production environment
- Orchestrate solution services
- Control the launch of the solution
- Automate deployment and monitoring of new versions of the solution
- Competency block 4: Manage a data management architecture project
- Define the organizational structure of the technical data management architecture project
- Supervise the development of the data architecture project
- Manage the project budget
- Communicate project progress and results to stakeholders and management
- Evaluate Data Engineering project performance
- Train end-users to the solution
Careers’ Opportunities for the Master Data Engineer
- Data Engineer
- Data / big data engineer
- Data developer
- Machine learning engineer
- Big data development engineer
Admission requirements
- To qualify for certification, candidates entering the 1st year of the program must hold a level 6 RNCP diploma or qualification, or have validated 180 ECTS credits.
- Candidates must also have an understanding of SQL, Python and the Linux system, and be familiar with the profession targeted by the professional project. These notions are assessed by means of a placement test prior to entering the course.
