Freelancer profile translated to English.
Back to original languageAbout Vann
Data Engineer, Tech Lead in data engineering on Foundry (PySpark, TypeScript, data modeling, pipelines, and data lineage). Accustomed to critical environments, I have led end-to-end projects combining data quality, performance, automation, and new feature delivery. Technical leadership, analytical skills, and a sense of impact guide my work.
Tools:
Palantir Foundry, Databricks, Snowflake, DBT,
English
Fluent
French
Native or bilingual
Can work on-site
Paris (up to 40km)
Experience
- AIRBUSTech Lead Data EngineerAVIATION AND AEROSPACEMarch 2026 - May 2026 (2 months)Scoping Mission
- Led the strategic and technical scoping of the project, analyzing business needs and defining the target approach.
- Structured the methodology, key deliverables, and technical standards to ensure execution.
- Supervised and validated the data model to guarantee a coherent, scalable, and business-aligned architecture.
- Provided technical leadership to guide choices, challenge the team, and ensure the quality of future implementations.
- StellantisTech Lead Data EngineerAUTOMOBILESeptember 2022 - February 2026 (3 years and 5 months)Poissy, France
- Technical leadership and preparation of new features: Drafted comprehensive technical specifications (new features, evolutions, data migrations), scoped needs, and defined requirements to ensure robust and scalable integration.
- Data integration and transformation: Merged, structured, and normalized data to ensure its consistency and availability within the Foundry ecosystem.
- Development of data-driven features: Designed and implemented new business and technical logic, working on code (PySpark, TypeScript), Foundry configuration, and data model design and evolution.
- Data incident investigation and resolution: End-to-end analysis, precise diagnosis, sustainable correction, and continuous improvement of pipelines to limit recurrence.
- Pipeline and data lineage optimization: Industrialized, improved performance, refactored, and monitored lineage to provide clear visibility into data flows.
- Visualization and analysis: Produced and maintained visualizations using Workshop, Contour, and Ontology Manager to facilitate data understanding and utilization.
- Success example: Major migration of a quality dataset, including data lineage redesign and integration of new business logic—a structuring project that improved data flow reliability and reduced incidents related to old structures.
- CapgeminiData EngineerDIGITAL AND ITMay 2022 - June 2026 (4 years and 1 month)Issy-les-Moulineaux, FranceConsultant involved in scoping, architecture, and implementation of data solutions.Technical leadership, modeling, pipeline development, data lineage optimization, and team support in complex environments (Palantir Foundry, PySpark, TypeScript, Snowflake).
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Education
- Master Big Data and Social AnalysisCNAM2019Business intelligence, Data visualisation, algorithme du traitements de données, machine learning, RGPD, Python, R, Qgis, Cassandra, Neo4j, MongoDB, SQL
- Professional Bachelor's Degree in Data MiningU-PEM2016Système d’information, gestion de projet, algorithme machine learning (régression, classification), machine learning, R, Microsoft BI, Oracle, SAS
Certifications
- Google Data Analytics CertificateCoursera2021