Reference code: JR129207
Richemont owns some of the world’s leading luxury goods Maisons, with particular strengths in jewellery, fine watches and premium accessories. Each Maison represents a proud tradition of style, quality and craftsmanship and Richemont seeks to preserve the heritage and identity of each of its Maisons. At the same time, we are committed to innovation and designing new products which are in keeping with our Maisons’ values, through a process of continuous creativity.
YOUR MISSION:
As the Logistics Data & Analytics Engineer, you will play a crucial role in transforming raw logistics data into actionable insights and robust data products. You will bridge the gap between complex data systems and business needs, ensuring that Logistics performance is accurately measured, understood, and optimized. This position combines the precision of a reporting analyst with the technical expertise of an analytics engineer, driving data-informed decision-making and continuous improvement across our global logistics operations, while fostering collaboration and advocating for the Group Logistics team.
HOW WILL YOU MAKE AN IMPACT?
Logistics Data Strategy & Performance Insights:
- Define, develop, and evolve comprehensive business reporting, dashboards, and Key Performance Indicators (KPIs) for Group Logistics.
- Conduct in-depth analysis of logistics data to identify trends, performance drivers, and areas for optimization.
- Act as the primary contact for interpreting logistics activity and performance indicators, fostering cross-regional collaboration.
- Support Group Logistics Financial Controller in the elaboration of financial KPIs and the maintenance of cost allocation keys.
Data Model & Product Engineering for Logistics:
- Partner with Logistics stakeholders to understand data needs, translating them into robust data model designs and actionable data products.
- Build, maintain, and optimize scalable data models and pipelines within cloud data warehouses (e.g., Google Cloud Platform - BigQuery), applying software engineering best practices (e.g., dbt, Git).
- Develop and manage data transformation logic using SQL.
Data Governance, Quality & Enablement:
- Ensure the accuracy, consistency, and integrity of logistics data by implementing rigorous data quality checks, validation processes, and comprehensive documentation.
- Leverage and manage analytics platforms (e.g., Looker, PowerBI) to create effective data visualizations and promote self-service analytics.
- Champion data literacy and a data-informed culture within Logistics, providing guidance, training, and support.
HOW WILL YOU EXPERIENCE SUCCESS WITH US?
Education:
- Master’s degree in Mathematics, Statistics, Engineering, Computer Science, Information Technology, or a related quantitative field; or an equivalent degree with a strong focus on Supply Chain Management or Logistics Performance.
Experience:
- Minimum 3 years of professional experience in data analytics, business intelligence, or data engineering, with a significant portion focused on logistics, supply chain, or operational analysis in an international environment.
- Proven experience in building and maintaining data models and developing advanced analytical solutions.
- Experience with cloud data warehouses (e.g., BigQuery).
Technical Skills:
- Expert proficiency in SQL programming and data modeling.
- Solid experience with data transformation tools such as dbt.
- Extensive experience with BI and data visualization tools (e.g., PowerBI, Looker).
- Familiarity with software engineering best practices, including Git for version control and CI/CD pipelines.
- Knowledge of SAP and other enterprise logistics systems is a strong asset.
- Proficiency in Python for data analysis is a plus.
Analytical & Business Expertise:
- Exceptional analytical, problem-solving, and critical thinking skills.
- Excellent knowledge of logistics activities, supply chain processes, and their associated KPIs.
- Ability to interpret performance results and provide strategic recommendations.
Interpersonal & Communication Skills:
- Outstanding interdisciplinary communication and collaboration skills.
- Ability to explain complex technical topics to diverse audiences, including non-technical stakeholders and top management.
- Proactive, autonomous, well-organized, rigorous, and adaptable in a fast-paced, constantly evolving environment.
- Demonstrated ability to manage multiple projects and priorities simultaneously.
- Strong team spirit, persuasive, and stakeholder-focused mindset.
Languages:
- Fluent in English (written and spoken) is mandatory. Proficiency in French is a strong advantage.
