- Location
- Office RIC - TOKYO Kojimachi 1-12-1 5F (JPTO0311), Japan
- Workplace
- Hybrid
- Type
- Full-time
- Seniority
- Lead
- Education
- Bachelor
- Source
- Workday
Description
Richemont, one of the world leaders in the luxury sector, has various Houses specializing in jewelry, watches and high-end accessories. Each Maison proudly embodies a tradition of style, quality and craftsmanship and Richemont strives to preserve the heritage and identity specific to each of them. At the same time, we are committed to innovating and designing new products in line with the values of our Houses, through a process of permanent creativity.
MAIN PURPOSE
This position leads data utilization and AI adoption in Japan. The role translates business needs into trusted, reusable data products and manages the full lifecycle from planning and design through delivery, adoption, and continuous improvement.
KEY RESPONSIBILITIES
Data Products & Analytics
• Translate business needs into data product plans, designs, and deliverables
• Standardize key business metrics and data definitions to establish trusted data foundations
• Develop scalable, reusable, and maintainable data models and analytics solutions
Data Architecture & Integration
• Design data integration across CRM, marketing, cloud data warehouse, and BI environments
• Ensure the quality and consistency of data models, transformation logic, and semantic layers
• Promote the reuse of existing data assets and standard delivery patterns
Governance, Quality & Delivery
• Establish practical standards for data quality, access, security, and privacy
• Manage priorities, dependencies, risks, and delivery quality across data initiatives
• Support documentation, quality assurance, and effective transition into ongoing operations
Adoption & Collaboration
• Promote adoption through training, onboarding, and usage monitoring
• Collaborate with business functions, technical teams, global and regional teams, and external partners
• Coach team members and transfer knowledge to strengthen internal data capabilities
COMPETENCIES AND EXPERIENCES
• Six or more years of experience in data, analytics, data engineering, or a related field, or equivalent practical experience
• Strong hands-on experience in data modelling and SQL
• Experience delivering solutions using cloud data warehouses, transformation tools, and BI or semantic-layer technologies
• Experience translating business needs into scalable data solutions
• Experience leading cross-functional initiatives
• Knowledge of data governance, quality, access management, and security
• Experience with BigQuery, dbt, Looker, or comparable platforms is preferred
• Business-level English and native-level Japanese
• Bachelor's degree in a relevant field or equivalent experience
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