Data Engineer - Gen AI - Finance (h/f) (IT)

Vous êtes un ingénieur de données expérimenté, spécialisé dans l'IA générique et Python ? emagine vous offre l'opportunité de rejoindre une équipe dirigée par emagine qui fournit des solutions basées sur l'IA dans un environnement bancaire international. Are you an experienced Data Engineer with expertise in Gen AI and Python? emagine has an opportunity for you to join an emagine-led team delivering AI-driven solutions within a global banking environment. You will play a key role in building on-prem AI tools that process and model large volumes of unstructured data from sources such as legal documents and financial policies. This is a hands-on role requiring strong technical skills and the ability to design efficient data pipelines for Gen AI applications. Main Responsibilities Design and implement data ingestion pipelines for structured and unstructured data. Apply techniques such as vectorization and chunking to prepare data for LLM-based solutions. Develop Python-based tools for large-scale data processing and storage manipulation. Collaborate with Data Scientists and Business Analysts to ensure data readiness for AI models. Key Requirements 5+ years of experience as a Data Engineer in complex environments. Strong expertise in Python and experience with data modelling for AI applications. Familiarity with vectorization, chunking, and handling large datasets. Knowledge of tools such as PySpark, MongoDB, graph databases, SparkleDP. Self-driven, proactive, and comfortable working in a fast-paced environment. Fluent in English Nice to Have Exposure to legal or procedure-focused applications. Other Details: This position is Hybrid ? on-site minimum 3 days per week in Paris 8th arrondissement. Apply with your latest CV or reach out to Brendan to find out more. Profil candidat: Plus de 5 ans d'expérience en tant qu'ingénieur de données dans des environnements complexes. Solide expertise en Python et expérience dans la modélisation de données pour les applications d'IA. Connaissance de la vectorisation, du découpage en morceaux et du traitement de grands ensembles de données. Connaissance d'outils tels que PySpark, MongoDB, les bases de données graphiques, SparkleDP. Autonome, proactif et à l'aise dans un environnement en constante évolution. Maîtrise de l'anglais