Data Ingenieur (e) F/H
EDF · Palaiseau, Île-de-France, France
- On site
- Full-time
- €60,000 / year
- Palaiseau, Île-de-France, France
Job highlights
- Configure and optimize data infrastructures for diverse users.
- Manage data collection, storage, and manipulation processes.
- Ensure production data flow monitoring and application operation.
- Integrate AI and ML models into data pipelines.
- Work with cloud platforms and Big Data technologies.
About the role
About EDF R&D and the SEQUOIA Department
At the intersection of essential challenges, join EDF, an internationally recognized group committed to the energy transition. Within EDF R&D at the EDF LAB Paris Saclay site, our mission is to contribute to the performance of the group's operational units. You will join the SEQUOIA department, specifically the 'Customer Consumption Analysis, Supply Offers' group, composed of about twenty research engineers.Your Missions
- Configure infrastructures appropriately and optimally for users who manipulate data.
- Identify constraints and technical components for collecting, storing, and manipulating data from various internal or external sources.
- Make data available by organizing it optimally for Data Scientists, Data Analysts, or various developers who will process the data.
- Ensure the operation and monitoring of data flows and applications deployed in production.
- Structure databases (semantic, format, etc.) within the data lake as needed.
- Participate in Proofs of Concept (POCs) to test and qualify new solutions proposed by IT services, depending on ongoing activities.
- Proactively suggest improvements to the technical foundation (data access, integration, storage, and valorization) when components become obsolete.
- Leverage AI to master tools and technologies for optimizing data flows, including real-time data processing systems and the integration of AI algorithms into data pipelines.
- Work on automating large-scale data management and with architectures adapted to increasingly complex Machine Learning and Deep Learning models.
Qualifications and Desired Skills
- Education: Bac+5 (Engineering degree, Master's in Applied Mathematics, Statistics, Artificial Intelligence, or Data Engineering).
- Technical Skills: Data modeling, data quality assurance with monitoring indicators, relational or NoSQL databases, Big Data storage and processing, automated data flows using ETL tools, programming (specifications, design, development, testing).
- Cross-functional Skills: Communication, problem-solving, project management.
- Tools: Data analysis and visualization tools (PowerBI, Dash, Grafana, Kibana), Cloud platforms (Amazon AWS, Microsoft Azure, Google Cloud Platform).
- Experience: Previous experience is appreciated.
- Additional Advantage: Knowledge in data science and experience in Big Data processing.
Key skills/competency
- Data Engineering
- Big Data
- ETL
- Data Modeling
- Data Warehousing
- Cloud Platforms (AWS, Azure, GCP)
- Data Visualization
- Python/SQL
- Machine Learning
- Data Pipelines
Skills & topics
- Data Engineer
- Data Engineering
- Big Data
- ETL
- Data Modeling
- Cloud Computing
- AWS
- Azure
- GCP
- Data Pipelines
- AI
- Machine Learning
- Data Visualization
- SQL
- NoSQL
- Energy Sector
- R&D
How to get hired
- Tailor your resume: Highlight your experience with Big Data, ETL, data modeling, and cloud platforms like AWS, Azure, or GCP, emphasizing your Bac+5 qualification and any relevant project experience.
- Showcase technical skills: Clearly list your proficiency in programming (Python/SQL), NoSQL/relational databases, data visualization tools (PowerBI, Grafana), and ETL processes.
- Demonstrate problem-solving: Prepare examples of how you've identified technical constraints, optimized data flows, and contributed to innovative data solutions.
- Emphasize AI/ML interest: Mention any exposure to AI, Machine Learning, or Deep Learning applications within data engineering contexts, showing your forward-thinking approach.
- Network and research: Understand EDF's commitment to the energy transition and R&D initiatives to align your application with their mission.
Technical preparation
Master Big Data tools and ETL processes.,Practice SQL and NoSQL database management.,Build data pipelines on cloud platforms.,Develop data visualization dashboards.
Behavioral questions
Describe optimizing a complex data flow.,How do you collaborate with data scientists?,Share an example of proposing new tech.,How do you monitor production data applications?
Frequently asked questions
- What specific data engineering tools does EDF R&D value for this Data Engineer role?
- For this Data Engineer position at EDF R&D, strong familiarity with cloud platforms like Amazon AWS, Microsoft Azure, and Google Cloud Platform is highly valued. Additionally, expertise in data analysis and visualization tools such as PowerBI, Dash, Grafana, and Kibana is sought after, alongside proficiency in ETL tools for automated data flows.
- What is the expected experience level for the Data Engineer position at EDF R&D?
- While a first experience in data engineering is appreciated, EDF R&D is open to candidates with a strong academic background (Bac+5) and relevant technical skills. Demonstrated project work, internships, or academic specializations in data engineering, AI, or Big Data can significantly strengthen your application even with limited professional experience.
- How does EDF R&D integrate Artificial Intelligence into the Data Engineer role?
- The Data Engineer at EDF R&D will work with AI by mastering tools and technologies that optimize data flows in direct relation to AI. This includes managing real-time data processing systems and integrating AI algorithms into data pipelines, supporting the development of complex Machine Learning and Deep Learning models.
- What are the key responsibilities of a Data Engineer within the EDF R&D SEQUOIA department?
- The Data Engineer will be responsible for configuring and optimizing data infrastructures, identifying technical solutions for data collection and storage, organizing data for analysis, monitoring data flows, structuring databases in a data lake, and participating in POCs for new data solutions. They will also focus on automation and adapting architectures for AI/ML models.
- Does EDF R&D encourage proposing new technical solutions for data management?
- Yes, EDF R&D actively encourages its Data Engineers to be proactive. You will be expected to propose improvements and new solutions for the technical foundation of data management, including access, integration, storage, and valorization, especially as components become obsolete or new technologies emerge.