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IDEMIA

Senior Data Engineer

IDEMIA

Contribute to IDEMIA's enterprise Data Platform and GenAI Platform on AWS. Collaborate with teams to build and maintain scalable data products and pipelines.

Posted 7/7/2026full-time🇫🇷 FranceSeniorWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in building and optimizing scalable data products and pipelines on AWS, with a strong focus on DataOps practices and AI technologies. Proficient in ensuring data quality, governance, and performance while collaborating with cross-functional teams to support analytics and generative AI initiatives.

Highest-signal resume keywords
AWSApache SparkData EngineeringDataOps PracticesGenerative AI

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Data Pipeline DevelopmentETL ProcessesBatch ProcessingReal-Time ProcessingData Quality Assurance
Soft Skills
CollaborationCommunication
Tools & Technologies
CI/CDInfrastructure-as-CodeObservabilityData MeshMLOps
Certifications & Qualifications
Master's Degree
Industry Keywords
Data ProductsAI SolutionsData GovernanceData LineageStreaming Architectures

Tech Stack

Tools & technologies
ApacheAWSETLKafkaSpark

About the role

Key responsibilities & impact
  • Contribute to the design, development, and operation of IDEMIA's enterprise Data Platform and GenAI Platform on AWS
  • Build scalable data products, industrialize data pipelines, and support the development of AI and Generative AI capabilities across the Group
  • Design, develop, and maintain scalable batch and near real-time data pipelines
  • Build and optimize ETL/ELT processes on AWS and Apache Spark
  • Develop and maintain data products supporting Analytics, BI, Data Science, and GenAI use cases
  • Contribute to the evolution of IDEMIA's Lakehouse architecture
  • Ensure data quality, governance, lineage, security, and performance
  • Participate in the development of the enterprise GenAI platform
  • Collaborate with Data Scientists and AI Engineers to industrialize AI and GenAI solutions
  • Contribute to CI/CD, Infrastructure-as-Code, observability, and DataOps best practices

Requirements

What you’ll need
  • Master's Degree (Engineering School or University)
  • 5+ years of experience in Data Engineering
  • Strong experience with AWS, Spark, and modern data platforms
  • Solid software engineering mindset and DataOps practices
  • Interest in AI and Generative AI technologies
  • Fluent English required
  • Nice to Have: Experience with Kafka or streaming architectures
  • Knowledge of Data Mesh and Data Products
  • Experience with MLOps or GenAI platforms
  • Exposure to enterprise AI solutions on AWS

Benefits

Comp & perks
  • Inclusive environment
  • Professional development opportunities
  • Accommodation during the recruitment process