Rolex Data Engineer
- Location
- GenevaGenevaSwitzerland
- Seniority
- Mid-Level
- Department
- IT & Technology Systems
- Industry
- Fine Watches & Horology
- Posted
- May 16, 2026
About Rolex
Rolex is a leading Swiss watchmaker renowned for its technical excellence, precision manufacturing and discreet global prestige. As an independent luxury maison, Rolex combines artisanal horology with advanced engineering and a long-term orientation toward quality, innovation and rigorous internal standards.
Rolex in Geneva seeks a Data Engineer to design scalable data pipelines and analytics platforms. Apply to join a precision-driven horology team.
Role & Responsibilities
- Design, develop and operate robust, scalable data pipelines and ETL workflows to consolidate operational and product data for analytics and reporting.
- Collaborate with data scientists, BI analysts and business stakeholders to translate analytical requirements into reliable data models and ingestion patterns.
- Implement and maintain data platform components, including batch and streaming architectures, ensuring data quality, lineage and observability.
- Optimize data storage and query performance across warehouses and lakehouse architectures; enforce best practices for partitioning, compression and schema design.
- Build and maintain CI/CD pipelines, infrastructure-as-code and deployment processes for data services to ensure repeatability and governance.
- Define and implement monitoring, alerting and incident-response procedures for data platform availability and correctness.
- Produce technical documentation, data contracts and onboarding materials for downstream consumers and cross-functional teams.
- Contribute to the continuous improvement of platform architecture, tooling standards and data security controls in compliance with corporate policies.
Qualifications
- Proven track record delivering production-grade data pipelines and data platform components.
- Strong proficiency in SQL and programmatic data engineering using Python or Scala.
- Experience with modern data processing frameworks (e.g., Apache Spark) and orchestration tools (e.g., Apache Airflow).
- Familiarity with cloud data services and object storage (examples: AWS S3, Redshift, Snowflake) and containerization (Docker, Kubernetes).
- Solid understanding of data modelling, ETL patterns, data quality practices and observability.
- Excellent problem-solving skills, attention to detail and ability to communicate technical concepts to non-technical stakeholders.
Skills
Experience
Typically 3+ years of hands-on experience in data engineering, building and operating ETL/ELT pipelines, data warehouses and analytics platforms in production environments.
Education
Bachelor's or Master's degree in Computer Science, Engineering, Data Science or a related technical discipline preferred.
Workplace
The role is situated in Geneva, Geneva, Switzerland.
Culture
Rolex cultivates a culture of technical excellence, precision and discretion, reflecting the maison's commitment to craftsmanship and long-term quality. Teams operate with high standards, close collaboration between engineering and product specialists, and a focus on sustainable, rigorously tested solutions.
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 Rolex, 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», «Analytics Engineer», «Data Infrastructure Engineer», «ETL Engineer», «Big Data 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.