Analytics Engineer Intern

Overview

Richemont is a Swiss-based luxury goods group comprising a portfolio of prestigious maisons across jewellery, watches, fashion and accessories. As an employer, the group combines heritage craftsmanship with an increasingly data-driven approach to retail and client engagement across global markets.

Role & Responsibilities

• Design, build and optimise data pipelines to transform raw transactional and behavioural data into analytics-ready datasets.
• Implement and maintain ETL/ELT workflows, ensuring data quality, lineage and performance for reporting and modelling needs.
• Collaborate with data scientists, BI analysts and commercial teams to translate business questions into robust data models and reusable assets.
• Develop and document dimensional models, metrics definitions and data catalog entries to ensure consistent analytics across the organisation.
• Support dashboard development and ad‑hoc analysis by preparing curated datasets and SQL-based extracts.
• Contribute to testing, monitoring and incident resolution processes for analytics platform components.

Qualifications

• Currently enrolled in a Bachelor's or Master's programme in Computer Science, Data Science, Statistics, Engineering, Mathematics or a closely related discipline.
• Practical experience writing complex SQL queries and working with relational or columnar data stores.
• Hands‑on experience in a general purpose programming language used for analytics (Python preferred).
• Familiarity with data modelling concepts, ETL/ELT patterns and software engineering best practices (version control, testing).
• Strong analytical reasoning, attention to detail and the ability to communicate technical concepts to non-technical stakeholders.

Skills

Experience

Practical project or internship experience building data pipelines, preparing datasets for analysis, or contributing to BI/analytics projects. Demonstrable coursework or independent projects that showcase end-to-end data work (ingestion, transformation, modelling, and delivery) are expected.

Education

Enrolled in a relevant undergraduate or graduate programme (Computer Science, Data Science, Engineering, Mathematics, Statistics or equivalent).

Culture

Richemont blends traditional luxury craftsmanship with modern, data-led decision making, fostering a collaborative environment that values precision and creativity. Teams are cross-disciplinary, working closely with commercial and product functions to translate heritage brand values into measurable customer experiences.