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OPEN

Data Engineer

OPEN

. Design, develop, and maintain robust, production-grade data pipelines.

Posted 11/6/2026full-timeNantes • FranceMid-LevelSeniorWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in designing and maintaining data pipelines, ensuring data quality and performance while leveraging Cloud environments. Proficient in Python, SQL, and data processing architectures to deliver business value through data solutions.

Highest-signal resume keywords
Data Engineering ExperiencePython ProficiencySQL ProficiencyData Processing ArchitecturesCloud Environments (Azure, AWS, GCP)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Data Pipeline DesignData IngestionData TransformationData Serving ProcessesData Quality AssuranceDataOps AutomationETL/ELT ToolsSparkPySparkData Lake/Warehouse Environments
Soft Skills
Detail-OrientedCollaborativeProblem-Solving
Industry Keywords
Data GovernanceData ArchitectureData LakesData WarehousesData Best Practices

Tech Stack

Tools & technologies
AWSAzureCloudETLFluxGoogle Cloud PlatformPySparkPythonSparkSQL

About the role

Key responsibilities & impact
  • Design, develop, and maintain robust, production-grade data pipelines.
  • Implement data ingestion, transformation, and serving processes.
  • Contribute to the design and evolution of Data architectures, including Data Lakes, Data Warehouses, and Lakehouses.
  • Ensure data quality, reliability, and traceability.
  • Optimize data processing performance and the management of large data volumes.
  • Automate and industrialize data flows following a DataOps approach.
  • Work closely with business teams, Data Analysts, Data Scientists, and technical teams.
  • Contribute to the continuous improvement of data governance, quality, and operational practices.
  • Join a team comprising Data Engineers, Data Analysts, Data Architects, and Cloud experts.
  • Contribute to architecture decisions, Data best practices, and the evolution of platforms.

Requirements

What you’ll need
  • At least 4 years of experience in Data Engineering.
  • Proficiency in Python and SQL.
  • Experience with data processing architectures and analytics platforms.
  • Ideally, knowledge of Spark, PySpark, ETL/ELT tools, and Data Lake or Data Warehouse environments.
  • Comfortable working with Cloud environments (Azure, AWS, or GCP).
  • Strong technical expertise and a keen awareness of data quality and performance challenges.
  • Autonomous, detail-oriented, and comfortable working in collaborative environments.
  • Enjoy solving complex problems and delivering business value through data.

Benefits

Comp & perks
  • Training, certifications, and personalized support.
  • Career development opportunities toward roles such as Lead Data Engineer, Data Architect, or Data Expert.
  • A dynamic technical community that encourages knowledge sharing.
  • A rapidly growing Data team with strong opportunities for development.