Senior Data Engineer for AI & GenAI Platform on AWS

Jobtailor; France; Sur place; EUR 65 000 - 90 000; Plein temps

Résumé du poste

IDEMIA is seeking a senior data engineer to contribute to the design, development, and operation of the enterprise Data Platform and GenAI Platform on AWS. You will build scalable data products and pipelines, supporting AI and GenAI capabilities across the Group.

You will work with Data Scientists and AI Engineers, industrialize AI/GenAI solutions, and drive CI/CD, observability, and data governance to ensure quality and performance across data products.

Qualifications

• Master's degree in engineering or equivalent.
• 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.

Responsabilités

• 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 AI/GenAI 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 data products supporting Analytics, BI, Data Science, and GenAI use cases.
• 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.

Connaissances

AWS

Apache Spark

Data Mesh

DataOps

GenAI

Formation

Master's Degree

Outils

Kafka

Description du poste

IDEMIA is seeking a senior data engineer to contribute to the design, development, and operation of the enterprise Data Platform and GenAI Platform on AWS. You will build scalable data products and pipelines, supporting AI and GenAI capabilities across the Group.

You will work with Data Scientists and AI Engineers, industrialize AI/GenAI solutions, and drive CI/CD, observability, and data governance to ensure quality and performance across data products.