Data Engineer (H/F)

About the Role

Hermès is deploying a new generation cloud Data Platform in the United States. You will be one of the first engineers to lay its technical foundations on the ground. Hermès is undertaking a migration of its local data platforms. This VIE role in the US will be responsible for data engineering tasks related to this transformation. You will not be joining a project in a maintenance phase. You will also form an operational partnership with the VIE Data Analyst on the same program; one builds the foundations, the other leverages them, and both roles are inseparable. This position is for a rigorous and structured profile, capable of building solid and sustainable solutions. In a high-stakes migration program, the quality and traceability of deliverables take precedence over speed of execution.

Key Responsibilities

• Local Standards & Best Practices:
• Act as a local liaison for defined architecture patterns, methodologies, standards, and best practices, ensuring their adoption and adherence in all development efforts.
• Pipeline & Ingestion:
• Design and develop data pipelines from US local sources to Snowflake (using dbt, SQL).
• Ensure the quality, reliability, and traceability of data flows: testing, documentation, GitLab CI/CD versioning.
• Participate in the evolution of the Data Platform schema in conjunction with the Data & AI Platform teams.
• Adhere to the retail core model already deployed in other geographic regions.
• Modeling & Datamarts:
• Model business datamarts in compliance with target data models defined by management.
• Structure transformation layers according to dbt standards and Hermès conventions.
• Document models and contribute to the data catalog: descriptions, lineage, compliance tests.
• Migration & Consistency:
• Map existing data sources on local platforms and establish their correspondence with new models.
• Identify and address discrepancies in definitions or granularity between source and target systems.

Requirements & Tech Stack

• SQL (advanced) and good relational modeling practices (Star/Snowflake schema).
• dbt (Core or Cloud): models, tests, documentation, macros.
• Snowflake or equivalent cloud data warehouse (BigQuery, Redshift).
• GitLab CI/CD: versioning and continuous integration practices.
• A proficiency in Power BI or another BI tool is a plus.

Qualifications

• Bac+5 degree in computer science, data engineering, applied mathematics, or equivalent.
• First significant experience (long-term internship, work-study, or initial assignment) in data engineering or analytics engineering.
• Rigor, oral fluency, proactivity.
• Professional English proficiency (written and oral) is essential; French is an asset.