Data Analyst

Data Analyst at Hermès

Share a human adventure at the heart of the hermes.com team.

Hermès currently offers an e-commerce platform across 34 sites, providing its customers with an omnichannel sales experience. Managed with an agile approach, this platform is part of a strategic and international program.

The digital professions at Hermès are organized around four dynamic and interconnected poles: e-commerce, digital operations, technology, and data performance. Just as an artisan crafts a bag from start to finish, the digital teams are involved from strategic thinking to project implementation.

Joining Hermès Digital means participating in a unique, integrated, and 100% agile project within a context of strong growth and international deployment. It means evolving in an environment that combines the most effective languages, technologies, infrastructures, tools, and methods on the market.

Job Description:

As a Data Analyst, you will join the Data & Performance team, responsible for collecting, transforming, and analyzing Hermès' digital data. Reporting to the Lead Data Analyst, you will primarily work on the Google Cloud Platform (GCP) and support central teams and subsidiaries to enable them to fully leverage digital data.

Main Activities:

• Creation and Management of Dashboards: Design, develop, and maintain clear and high-performing dashboards in Looker Studio (and potentially Power BI) for business teams and subsidiaries. Ensure the consistency, reliability, and freshness of key performance indicators (KPIs). Identify user needs and evolve dashboards according to business priorities.
• Data Analysis and Interpretation: Explore data from the Hermès Data Warehouse (BigQuery) using SQL queries. Conduct in-depth analyses to understand the performance dynamics of hermes.com: sales, traffic, customer journey, acquisition, loyalty, etc. Produce actionable insights and reports to support strategic and operational decision-making. Collaborate closely with Digital, Business, and subsidiary teams to help them leverage data daily.
• Analytics Engineering & Data Quality: Contribute to the reliability and structuring of data within the Data Warehouse, in conjunction with Data Engineering teams. Participate in data modeling and transformation in dbt to ensure the consistency and traceability of indicators used in analyses and dashboards. Monitor the quality and freshness of datasets, and alert in case of anomalies or flux breaks. Ensure compliance with confidentiality and privacy principles: oversee GDPR compliance, data anonymization, and security of handled data.

Profile Sought:

• Experience and Education: Minimum of 3 years of experience in data analysis. Master's degree (Bac +5) in Engineering School, Business School, Big Data Master's, Mathematics/Statistics, or equivalent. Sensitivity to digital and e-commerce challenges.
• Desired Qualities: Organized, rigorous, curious, autonomous. Excellent written and oral communication skills, interpersonal skills, team spirit. Good level of English (spoken and written) for international communication. Ability to self-learn, particularly in technical aspects.
• Technical Skills and Tools:
  • BI/Data Visualization Tools: Essential mastery of Google Looker Studio, Power BI, or equivalents.
  • SQL: Solid experience in data manipulation (BigQuery, MySQL, Redshift, Snowflake, etc.).
  • ETL/Data Transformation: Experience with tools like dbt, Dataform, or Dataiku.
  • Web / Product Analytics: Knowledge of web data analysis (Google Analytics 4, Piano, Content Square, Mixpanel, Amplitude...) is highly appreciated.
  • Programming Languages: Knowledge of Python is a plus.
  • Machine Learning: Basic knowledge is appreciated.

Benefits for You:

• Join the Maison Hermès, artisan of exceptional products!
• Be at the heart of an exciting project.
• Join a supportive team focused on data quality and member development.
• Enjoy significant autonomy and encouraged initiative-taking.

Key skills/competency:

• Data Analysis
• SQL
• Looker Studio
• BigQuery
• dbt
• E-commerce Analytics
• Digital Data
• Data Visualization
• Data Quality
• Business Intelligence