Data Engineer Apprentice: Governance & Pipelines (Paris)

Faurecia; Paris; Sur place; EUR 16 000 - 20 000; Temps partiel

Résumé du poste

Forvia in Paris is seeking a Data Engineer apprentice to join the Data Governance team. You will design, build, and maintain data integration pipelines, focusing on Palantir and MS Fabric, while upholding data quality and governance standards.

The role requires a Master's degree in CS or Data Engineering, knowledge of big data ecosystems, Python, SQL/NoSQL, and good English/French communication; collaboration with IT architects and data teams is essential.

Qualifications

• Master’s degree in Computer Science, Data Engineering or related field.
• Experience building data models, data mining and segmentation.
• Strong knowledge of Spark and Hadoop ecosystems.
• Proficiency in Python and data governance.
• SQL and NoSQL databases knowledge.
• Palantir knowledge is a plus.
• Fluent in English and French.
• Good analytical thinking.

Responsabilités

• Design, develop, and maintain data integration pipelines, particularly within Palantir and MS Fabric
• Ensure data quality, consistency, and governance compliance
• Contribute to development of applications and tools supporting Data Governance network
• Create ontologies for knowledge and data management
• Collaborate with business owners, IT Architects & Data teams

Connaissances

Data modeling

Data mining

Big data ecosystems

Python

SQL/NoSQL

Palantir

English communication

French communication

Analytical thinking

Formation

Master's degree in Computer Science or Data Engineering

Outils

Palantir

Description du poste

Forvia in Paris is seeking a Data Engineer apprentice to join the Data Governance team. You will design, build, and maintain data integration pipelines, focusing on Palantir and MS Fabric, while upholding data quality and governance standards.

The role requires a Master's degree in CS or Data Engineering, knowledge of big data ecosystems, Python, SQL/NoSQL, and good English/French communication; collaboration with IT architects and data teams is essential.