Richemont Logistics Data & Analytics Engineer
- Employment
- Full-Time
- Seniority
- Mid-Level
- Department
- Supply Chain, Logistics & Inventory
- Posted
- May 27, 2026
About %s
Richemont is a global luxury goods conglomerate headquartered in Switzerland, with an extensive portfolio spanning high jewelry, watches, eyewear, and fine leather goods. The group operates through prestigious maisons including Cartier, Van Cleef & Arpels, Piaget, IWC Schaffhausen, and Panerai. Richemont is recognised for its commitment to craftsmanship, heritage, and innovation within the luxury sector, leveraging advanced technology to enhance operational excellence across its global supply chain and retail networks.
Richemont seeks a Logistics Data & Analytics Engineer in Villars-sur-Glâne to optimise supply chain through advanced analytics and data engineering solutions.
Role & Responsibilities
- Design and develop data pipelines and ETL processes to consolidate logistics data from diverse systems across the global supply chain
- Create advanced analytics dashboards and visualisations to monitor KPIs, inventory levels, and operational performance metrics
- Identify process optimisation opportunities through statistical analysis and predictive modelling of supply chain data
- Collaborate with logistics, warehouse, and distribution teams to understand business requirements and translate them into technical solutions
- Maintain data quality, governance, and security standards throughout all analytics and engineering workflows
- Support continuous improvement initiatives by providing actionable insights and recommendations to supply chain leadership
Qualifications
- Advanced proficiency in data engineering tools and languages such as Python, SQL, or Scala
- Demonstrated experience with business intelligence platforms (Tableau, Power BI, Qlik, or equivalent)
- Strong understanding of data warehousing and data lake architecture
- Experience with cloud platforms (AWS, Azure, GCP) and big data technologies (Spark, Hadoop)
- Knowledge of supply chain, logistics, or operations is highly valued
Skills
Experience
3–5 years of professional experience in data engineering, analytics, or a related technical role, preferably with exposure to supply chain, logistics, or operations environments. Prior experience in a luxury goods, retail, or manufacturing context would be advantageous.
Education
Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, or a related quantitative discipline. Master's degree or advanced certifications in data engineering or analytics are desirable.
Workplace
This position is based in Villars-sur-Glâne, Fribourg, Switzerland, within easy reach of Fribourg.
Culture
Richemont fosters an environment where Swiss precision meets luxury excellence, emphasising data-driven decision-making and technological innovation. The company values analytical thinking, attention to detail, and collaborative problem-solving across its diverse global operations. With headquarters in Villars-sur-Glâne, Switzerland, the role benefits from working within a world-class logistics and supply chain infrastructure that serves the most discerning clientele.
About %s
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.
Frequently Asked Questions
The luxury industry is characterised by a diverse and nuanced nomenclature. Esteemed houses frequently employ proprietary terminology, and even within a single organisation like Richemont, titles may vary across global markets to reflect local conventions. To ensure absolute clarity, Cerulean assigns a standardised, industry-coherent canonical title to every listing. However, it is worth noting that this role is functionally synonymous with «Supply Chain Data Engineer», «Logistics Analytics Specialist», «Data Engineer - Supply Chain», «Logistics Intelligence Analyst», and other variations. Our sophisticated search architecture anticipates these variations, ensuring that inquiries using related terms will seamlessly yield the exact roles you desire.