Richemont Data Engineer
- Location
- Seniority
- Mid-Level
- Department
- IT & Technology Systems
- Industry
- Fine Watches & Horology
- Posted
- Apr 27, 2026
About Richemont
Donzé-Baume is a Swiss watchmaking maison based in Les Breuleux, operating within the high-precision segment of the horology supply chain. The brand emphasizes artisanal craftsmanship, technical excellence and the integration of modern engineering practices to support product quality and small-series manufacture.
Donzé-Baume — Data Engineer in Les Breuleux, Switzerland. Build and operate data pipelines, warehousing and analytics to support watchmaking operations.
Role & Responsibilities
- Design, build and maintain resilient data pipelines and ETL processes that consolidate production, quality, supply-chain and commercial data from on-premise and cloud sources.
- Develop and operate the company’s data platform and data warehouse to enable reporting, KPIs and advanced analytics for manufacturing and product teams.
- Implement robust data modelling, master data management and data quality controls to ensure accurate cross-functional reporting.
- Collaborate with production engineering, supply chain, R&D and finance to translate operational needs into scalable data solutions and dashboards.
- Automate data ingestion, transformation and scheduling; monitor pipeline health and resolve performance or integrity issues.
- Support deployment of analytics and predictive-maintenance use cases, including prototyping with data scientists and taking models to production.
- Define and apply data governance, access controls and documentation standards consistent with Swiss and EU data-protection expectations.
- Contribute to technical roadmap, vendor selection and the incremental modernization of the IT/data stack.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Data Science, Software Engineering, Industrial Engineering or equivalent technical discipline.
- Proven experience delivering end-to-end data solutions in production environments (data integration, modelling and warehousing).
- Comfort working in a small, cross-functional organisation and liaising with non-technical stakeholders in manufacturing and product teams.
- Strong analytical mindset with attention to data quality, lineage and operational reliability.
Skills
Experience
Typically 3+ years of professional experience in data engineering, data integration or a closely related role; experience within manufacturing, supply chain or industrial production environments is strongly preferred.
Education
Bachelor’s or Master’s degree in Computer Science, Data Science, Software Engineering, Industrial Engineering or a related technical discipline.
Workplace
The role is situated in Les Breuleux, Jura, Switzerland — conveniently close to La Chaux-de-Fonds.
Culture
The workplace reflects traditional Swiss watchmaking values—precision, patience and collective craftsmanship—combined with an openness to technical innovation. Collaboration across small, multidisciplinary teams and a pragmatic approach to problem-solving are central to daily life at the maison.
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.
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 «Data Platform Engineer», «Data Integration Engineer», «Analytics Engineer», «Business Intelligence Engineer», and other variations. Our sophisticated search architecture anticipates these variations, ensuring that inquiries using related terms will seamlessly yield the exact roles you desire.