Data Analyst

Hermès

On-sitePosted July 30, 2026

About the role

Context and Mission: As part of Hermès’ expansion of its Cloud Data Platform in the United States, Hermès is transforming its data assets. You will join this initiative at a pivotal moment when analytics foundations are being built. The VIE Data Analyst will ensure data are reliable, well-documented, and usable, partnering with US business teams and the Analytics & AI team at HDTI. You will also operate in tandem with the VIE Analyst Engineer on the same programme: one builds the foundations, the other unlocks value. This role requires a strong functional understanding of data: the ability to analyze datasets, interpret business meaning, identify anomalies, and document with rigor. Technical skills are a lever, but the ability to assimilate business processes is essential.

Data Analyst

Hermès

On-sitePosted July 30, 2026

About the role

Context and Mission: As part of Hermès’ expansion of its Cloud Data Platform in the United States, Hermès is transforming its data assets. You will join this initiative at a pivotal moment when analytics foundations are being built. The VIE Data Analyst will ensure data are reliable, well-documented, and usable, partnering with US business teams and the Analytics & AI team at HDTI. You will also operate in tandem with the VIE Analyst Engineer on the same programme: one builds the foundations, the other unlocks value. This role requires a strong functional understanding of data: the ability to analyze datasets, interpret business meaning, identify anomalies, and document with rigor. Technical skills are a lever, but the ability to assimilate business processes is essential.

Key Responsibilities: - Act as the local liaison for data analytics standards, methodologies, and best practices, ensuring adoption and compliance within the US team. - Exploration & documentation of the existing US data: establish a data diagnostic, produce data profiles and document anomalies and risk areas, creating the reference map of the data assets prior to migration; identify implicit business rules in existing data to feed target model; build the analytical memory of the project. - Data quality analysis & gap analysis: compare source data (local platform) to new data models on Snowflake, define scope and definitions, produce actionable gap analyses for engineering teams; formalize gaps and propose rules for reconciliation or transformation; monitor data quality indicators during migration. - Das

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Key Responsibilities: - Act as the local liaison for data analytics standards, methodologies, and best practices, ensuring adoption and compliance within the US team. - Exploration & documentation of the existing US data: establish a data diagnostic, produce data profiles and document anomalies and risk areas, creating the reference map of the data assets prior to migration; identify implicit business rules in existing data to feed target model; build the analytical memory of the project. - Data quality analysis & gap analysis: compare source data (local platform) to new data models on Snowflake, define scope and definitions, produce actionable gap analyses for engineering teams; formalize gaps and propose rules for reconciliation or transformation; monitor data quality indicators during migration. - Das