Data Engineer (H/F/NB)

About the Position

Data Engineer (H/F/NB)

Architect of Intelligence

Why Join Keyrus Today?

Keyrus is an international group of 2,800 consultants and experts present in 28 countries, driven by a strong belief: it's not artificial intelligence that transforms companies, but intelligence designed, structured, and integrated into their operations.

For over 30 years, we have been building the data foundations that enable intelligent systems to create value. We design the operating system of the intelligent enterprise, where data, AI, and human expertise integrate at the heart of business processes to generate sustainable performance. At Keyrus, we bring operational intelligence to life.

Artificial intelligence does not replace humans. It allows them to focus on what no system can replicate: understanding, deciding, designing, and innovating. Joining Keyrus means building your judgment, expertise, and ability to solve complex problems.

Technology is an accelerator. The Keyrus culture makes the difference. Operational excellence connects the two.

What Awaits You

• You design and industrialize robust data pipelines, from raw data to its exploitation by applications and agents.
• You deploy and operate modern data platforms (lakehouse, cloud warehouses) to make data accessible, governed, and performant at scale.
• You make data usable by generative and agentic AI systems (Anthropic, OpenAI, Mistral, Google Gemini, etc.): structuring for RAG, feeding vector databases, preparing datasets for model evaluation.
• You ensure data quality, freshness, and traceability through tests and data contracts, not just manual supervision.
• You quickly transform a mockup into a viable proof of concept to validate a use case before industrializing the final pipeline.
• You implement restitution (BI, dashboards) when the use case requires it, in addition to exposing data to agents.

What You Bring

The Architect of Intelligence Foundation: essential qualities present in the criteria below: curiosity, creativity, communication, professional conscience, culture, ability to do.

Experience and Background

• Significant experience in designing and industrializing data pipelines in production, regardless of your starting point: ESN, publisher, startup, or end customer.
• Proven practice of modern data platforms (cloud or lakehouse), beyond traditional ETL.
• Experience, if possible, in data preparation for generative or agentic AI systems.

Posture and Mindset

• Engineering rigor on data quality and reliability: unreliable data invalidates everything built on top.
• Curiosity for the uses enabled by the data you prepare, beyond the pipeline itself.
• Ability to collaborate with AI Engineers and Foundations Architects on data exposure to models and agents.
• Real autonomy to transform a poorly defined need into a viable proof of concept.
• Ability to produce, document, and transmit the pipelines you build, so they remain usable beyond your presence on the mission.

Essential Technical Skills

• Advanced proficiency in SQL, a non-negotiable foundation regardless of the dominant language.
• In-depth mastery of a pipeline language: Python as a priority, Java or Scala depending on the ecosystem (Spark, Kafka).
• Implementation of distributed processing with Apache Spark.
• Orchestration of data pipelines with Airflow or Dagster.
• Industrialized data transformation with dbt.
• Deployment and operation of cloud data platforms (Snowflake, BigQuery, Databricks).
• Design of streaming and real-time data processing architectures (Kafka), when the use case requires it.
• Use of vector databases for RAG use cases (Pinecone, Milvus, Chroma, or equivalent).
• Practical understanding of prompting and data preparation for language model evaluation (Anthropic, OpenAI, Mistral, Google Gemini, etc.).
• Implementation of tests and data contracts to ensure data quality and observability.
• Data modeling and preparation for analytical and operational uses.
• Rapid prototyping with lightweight tools (Streamlit) to transform a mockup into a viable proof of concept.
• Production, documentation, and transmission of pipelines, so they remain usable beyond your presence.
• Professional fluency in English, both written and spoken, essential regardless of experience level.

What Drives Us

Collective Intelligence

Collaboration between expertise, professions, and geographies allows us to combine know-how and provide more comprehensive answers to our clients' challenges.

Reliability

Our ability to deliver complex projects with rigor and high standards is one of the foundations of the trust relationship we build with our clients.

Pragmatism

We prioritize concrete impact and measurable value creation over abstract technological discourse.

Entrepreneurial Spirit

Curiosity, energy, and autonomy are at the heart of our culture. They foster initiative, innovation, and the continuous development of our expertise.

About Keyrus

At Keyrus, we support organizations in their transition from experimental AI to industrialized AI, from isolated agents to orchestrated systems, and from analysis to execution. This expertise is what we call Intelligence Architecture.

Thanks to our proprietary Human Orchestrated Model™ (HOM), we design intelligent environments based on three fundamental pillars: robust and reliable data and intelligence foundations; governance ensuring that humans remain at the heart of decision-making; performance monitoring mechanisms enabling continuous improvement.

With over 30 years of expertise and 2,800 employees in 28 countries, Keyrus supports companies far beyond their transformation.

Keyrus is listed on Euronext Growth Paris (ALKEY – ISIN Code: FR0004029411).

Department: Architect of Intelligence

Locations: Bordeaux, Nantes

Remote Status: Hybrid

Contract Type: CDI

Contact: Alexandra Damart, Senior International Talent Acquisition Expert

Salary: €40,000 - €60,000 per year

Core Skills: SQL, Python, Apache Spark, Airflow, dbt, Snowflake, BigQuery, Databricks, Kafka, Chroma, English

Secondary Skills: None

Employment Type: Contract

Experience Level: Middle

Languages: None

Categories: None

Work Location Type: Hybrid

Experience Evidence: Significant experience in designing and industrializing data pipelines in production

Experience Years: Not specified

Education Level: Not specified