Richemont Analytics Engineer

About Richemont

Richemont is one of the world’s foremost luxury groups, stewarding a distinguished portfolio of maisons across jewellery, watchmaking, fashion and accessories, including Cartier, Van Cleef & Arpels, Jaeger-LeCoultre and Montblanc. As an employer, it combines the heritage of artisanal excellence with a forward-looking culture shaped by innovation, client-centricity and responsible business. Its global teams operate in an environment that values craftsmanship, entrepreneurship and collaboration, offering opportunities to grow within iconic maisons and group functions alike. Richemont attracts professionals who aspire to contribute to enduring luxury, preserving rare savoir-faire while helping define the future of high craftsmanship.

The Analytics Engineer reports to the Data Enablement Manager and designs and maintains scalable data models and pipelines, enabling reliable reporting, advanced analytics, and data-driven decisions for Richemont Europe Functions and Markets. The role also supports business planning and regional forecasting, develops dashboards and insights, and contributes to AI Agent and automation initiatives.

Role & Responsibilities

• Design, develop, and maintain advanced data models supporting analytical needs across Functions and Maisons in Europe.
• Build, optimize, and manage ETL/ELT pipelines using SQL, Python, and other relevant tools to extract, load, and transform data from source systems into the data warehouse or lake.
• Implement data-quality checks, validation rules, and monitoring processes to ensure the accuracy, consistency, and reliability of data assets.
• Optimize data models and queries for performance and scalability, ensuring efficient data retrieval for reporting and analytical applications.
• Collaborate with Data Scientists, Business Analysts, and Data Engineers to understand data requirements, translate business logic into technical specifications, and deliver high-quality data solutions.
• Create and manage access rules for advanced data models.
• Create and maintain comprehensive documentation for data models, pipelines, and data dictionaries.
• Use and contribute to the development of modern data stack tools, including dbt and BigQuery.
• Identify and resolve data-related issues to ensure data availability and accuracy.
• Develop, maintain, and deploy dashboards that address identified business needs.
• Conduct in-depth analyses to address specific business needs and provide actionable insights.
• Train, accompany, and support business users in using analytics tools effectively.
• Support the preparation of budgets, strategic plans, business reviews, business development exploration, and operational forecasts.
• Contribute to data-related business projects to identify efficiencies, opportunities, and potential risks, such as commission schemes.
• Collaborate with senior engineers and data scientists to design and implement AI Agents using machine-learning techniques, including Large Language Models (LLMs).
• Drive the regional forecasting process, supporting the regional executive committee in budget preparation and local logistics operations in capacity planning.

Qualifications

• Strong proficiency in SQL for data manipulation, transformation, and querying.
• Experience with data warehousing concepts and technologies, such as Google BigQuery.
• Proficiency in a scripting language, preferably Python, for data processing and automation.
• Experience with data transformation tools; dbt (data build tool) experience is highly desirable.
• Familiarity with cloud platforms and their data services, such as GCP, AWS, or Azure.
• Understanding of data modeling techniques, such as the Kimball methodology.
• Experience with version control systems, such as Git.
• Strong analytical and problem-solving skills, with attention to detail.
• Ability to communicate effectively with technical and non-technical stakeholders.
• Ability to manipulate and condense large volumes of data into clear visualizations, including graphs, charts, diagrams, dashboards, and pivot tables.
• Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, Mathematics, or a related quantitative field.
• Relevant certifications in cloud data platforms or data engineering are a plus.

Skills

Education

Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, Mathematics, or a related quantitative field.

Workplace

Culture

Richemont fosters a refined, international workplace where its Maisons preserve exceptional craftsmanship while benefiting from the strength and perspective of a global luxury group. As an employer, it values long-term stewardship, collaboration, innovation, and the development of talent within an environment shaped by heritage, creativity, and high standards.

About Cerulean

Cerulean is the definitive career portal for the global luxury industry. We match exceptional professionals with exclusive opportunities at the world's most prestigious brands. From haute couture and fine watchmaking to prestige beauty, hospitality, and boutique retail, Cerulean centralises luxury employment to help you find the career for which you were destined.