DATA ENGINEER
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DATA ENGINEER
Meeting Group business lines’ Big Data needsDo you have a good grasp of computer languages and are you passionate about Big Data? Does the use of data represent the future for you? Good news: you will really be in your element within the Societe Generale Group as a Data Engineer!
In close collaboration with other IT experts (Data Scientists, Data Quality Managers, Data Designers, Big Data Architects) and all the Group’s business lines, you will work using the Agile method and in peer programming. You will collect, organise and model data; in a word, you will make it accessible. You will also conduct first-rate technology monitoring in order to ensure your data-related knowledge always remains up to date. All this will make you an indispensable expert, whose opinions are taken into account in Group decisions.
Your responsabilities
- To devise solutions to collect, organise and synthesise large volumes of data
- To take part in the complex analysis of data coming from different sources
- To conduct technology monitoring enabling new features and new tools to be tested, to attend various international conferences (Flink Forward, Spark Summit, etc.).
- To document your work
- To use data responsibly and ethically
HIGHLIGHTS OF THE JOB
A place at the heart of the Group’s digital transformation
Internal communities of experts with whom to exchange ideas
Numerous training courses to ensure your development within the data community
Use of innovative technologies
Meet Sébastien, Data Engineer specialized in AI
Hello everyone, my name is Sébastien, I am a Distinguished Engineer on data and artificial intelligence at Societe Generale since 2021, which I joined after spending about ten years in a large tech company to set myself a new challenge.
If I had to summarize in one sentence: my job is to guide strategic decisions in terms of technology and innovation. Of course, on a daily basis, it's a little more diverse and no two days are the same. Nevertheless, there are still three main pillars.
Firstly, it means defining and implementing the technical strategy of the Group's data and AI platforms, whether in terms of technologies, products, innovation and construction methods.
Secondly, it's managing projects at the cutting edge of innovation, such as, for example, the implementation of the Societe Generale Group's generative AI platform.
And thirdly, I participate in the acculturation of business lines to explain how the data and AI can improve their daily lives.
In my opinion, there are two key skills. The first is curiosity, because we are in a world where technology is fast-moving and very innovative.
The second is daring, because you also have to be able of thinking outside the box to create conditions for change and apply innovation on a daily basis.
Since a few years now, I have been coaching and mentoring of young technical talent, whether they are developers or data scientists.
I'm always very proud when I see them develop and fulfill their potential within the Group.
My team is international, based mainly in France and India.
In this context, it's extremely important to me to have an atmosphere where everyone feels free to express their opinions and ideas.
I also attach great importance to autonomy and initiative, because we are working in a field where innovation is key and so we have to give everyone the opportunity to be independent and to take his own initiatives.
When I arrived in the Group, what surprised me the most, it was both the appetite for technological innovation, while operating in a highly regulated sector so I was very pleasantly surprised to see how the Group managed to resolve this apparent contradiction to create innovations that are both responsible, but which also comply with the regulations in force.
If I had to summarize in one sentence: my job is to guide strategic decisions in terms of technology and innovation. Of course, on a daily basis, it's a little more diverse and no two days are the same. Nevertheless, there are still three main pillars.
Firstly, it means defining and implementing the technical strategy of the Group's data and AI platforms, whether in terms of technologies, products, innovation and construction methods.
Secondly, it's managing projects at the cutting edge of innovation, such as, for example, the implementation of the Societe Generale Group's generative AI platform.
And thirdly, I participate in the acculturation of business lines to explain how the data and AI can improve their daily lives.
In my opinion, there are two key skills. The first is curiosity, because we are in a world where technology is fast-moving and very innovative.
The second is daring, because you also have to be able of thinking outside the box to create conditions for change and apply innovation on a daily basis.
Since a few years now, I have been coaching and mentoring of young technical talent, whether they are developers or data scientists.
I'm always very proud when I see them develop and fulfill their potential within the Group.
My team is international, based mainly in France and India.
In this context, it's extremely important to me to have an atmosphere where everyone feels free to express their opinions and ideas.
I also attach great importance to autonomy and initiative, because we are working in a field where innovation is key and so we have to give everyone the opportunity to be independent and to take his own initiatives.
When I arrived in the Group, what surprised me the most, it was both the appetite for technological innovation, while operating in a highly regulated sector so I was very pleasantly surprised to see how the Group managed to resolve this apparent contradiction to create innovations that are both responsible, but which also comply with the regulations in force.
Profiles wanted
Skilled in IT development
Knowledgeable of Scala, Spark, Flink software, Python development
Used to database management
Effective with Agile development
5 years of higher education in IT, school of engineering or university
Frequently asked questions about Data Engineer
1.
What is a Data Engineer?
The Data Engineer is a data professional who plays a crucial role in managing, processing, and shaping collected data. They are responsible for building and maintaining the infrastructure necessary to collect, store and analyse large quantities of data. Lastly, the Data Engineer ensures the availability and quality of data for analyses carried out by the Data Analyst.
2.
What are the main tasks of a Data Engineer?
A Data Engineer’s job description includes the following tasks:
- designing and implementing data pipelines, a method that allows for the collection, transformation, and storage of data to be used in projects;
- cleaning and transforming data;
- developing and maintaining databases.
- implementing security measures to protect sensitive data and ensure compliance with existing regulations;
- monitoring and auditing data access to prevent security breaches and unauthorised access.
A Data Engineer is also responsible for data security and compliance, and he or she is assigned the following tasks:
Lastly, Data Engineers need to be constantly on the lookout for new technologies to enable innovation within their organisation, in order to improve the efficiency and quality of data management processes.
3.
What skills and qualities are essential to becoming a Data Engineer?
Becoming a data engineer requires the acquisition of solid and varied technical skills.
Data Engineers must master programming (Python, SQL) as well as various operating systems (UNIX, Linux, Solaris) and data processing tools (Hadoop, Spark). They must also have software engineering skills: mastering the design, development and updating of computer software. The Data Engineer must also have a good understanding of databases and their solutions (SQL, NoSQL). Mastery of Big Data technologies is also essential, as they enable massive volumes of data to be processed and handled
Lastly, to understand and meet the company's needs, the Data Engineer must be able to collaborate with all teams.
Data Engineers must master programming (Python, SQL) as well as various operating systems (UNIX, Linux, Solaris) and data processing tools (Hadoop, Spark). They must also have software engineering skills: mastering the design, development and updating of computer software. The Data Engineer must also have a good understanding of databases and their solutions (SQL, NoSQL). Mastery of Big Data technologies is also essential, as they enable massive volumes of data to be processed and handled
Lastly, to understand and meet the company's needs, the Data Engineer must be able to collaborate with all teams.
4.
What training is necessary to become a Data Engineer?
The training for a Data Engineer requires a master’s degree (in Data Science, Big Data or Artificial Intelligence, for example) from an engineering or computer science school.
Some companies require specific certifications, such as the Google Data Engineer certification (GDE), Google Cloud Platform Data Engineer certification (GCP) or Amazon Web Services Data Engineer certification (AWS). )
Finally, to stand out from other candidates, don’t hesitate to gain as much professional experience as possible during your studies.
Some companies require specific certifications, such as the Google Data Engineer certification (GDE), Google Cloud Platform Data Engineer certification (GCP) or Amazon Web Services Data Engineer certification (AWS). )
Finally, to stand out from other candidates, don’t hesitate to gain as much professional experience as possible during your studies.
5.
How does a Data Engineer’s career progress?
A data engineer can advance to positions with more responsibilities such as Lead Data Engineer, Big Data Architect ou Chief Data Officer.
They can also specialise in data design and become a Data Designer.
They can also specialise in data design and become a Data Designer.
6.
What is a typical day for a Data Engineer?
In a typical day, the Data Engineer participates in meetings with other company teams to understand their data needs. They manage and optimise data pipelines. They debug technical issues by fixing coding errors using a "debugger," a debugging software. Lastly, they seek solutions to improve data processing efficiency.
7.
What is the average salary of a Data Engineer?
The average salary of a Data Engineer varies according to experience, geographic location and the industry sector of the company they work for. For example, in France, a Junior Data Engineer can expect a salary of between €35,000 and €45,000 per year, while a more experienced Data Engineer can earn up to €60,000 per year.
8.
Data Engineer vs. Data Architect: What are the differences?
A Data Engineer builds and manages data infrastructures.
A Data Architect, on the other hand, designs and models data systems to meet various needs.
A Data Architect, on the other hand, designs and models data systems to meet various needs.
9.
Data Engineer vs. Machine Learning Engineer: What are the differences?
A Data Engineer manages data pipelines and infrastructures, while a Machine Learning Engineer focuses on development to deploy machine learning models and solve specific problems.
10.
Data Engineer vs. Data Scientist: What are the differences?
A Data Engineer manages data and data reading infrastructures, while a Data Scientist analyses and interprets data to enable the company to make informed decisions.
11.
Data Engineer vs. Data Analyst: What are the differences?
A Data Engineer manages data pipelines and infrastructures, while a Data Analyst analyses and interprets data to provide the best recommendations to the company.
How to join us
To get to know each other and make sure you will be happy as part of Societe Generale, please follow the below steps.
01
Get in touch
By responding to our job advertisement.
02
Tell us a little bit more about yourself
We’ll contact you for an initial exchange
and online tests.
03
Is it a match?
You’ll meet our operational team and human
resources partners.
04
Welcome!
The job is yours, and you’re ready to start the adventure.
The adventure has just begun!
At Societe Generale, we make sure that you can develop your career based on your ambition and abilities. After a position as a Data Engineer, you will have access to new opportunities such as:
- Data Scientist
- Data Designer
- Database Administrator
- Technical Architect
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