Moët Hennessy Data Project Assistant (Apprenticeship)
- Location
- ParisÎle-de-FranceFrance
- Employment
- Internship
- Seniority
- Intern
- Department
- IT & Technology Systems
- Industry
- Wines, Spirits & Gastronomy
- Posted
- May 5, 2026
About Moët Hennessy
Moët Hennessy is the wines and spirits division of LVMH, bringing together prestigious maisons such as Hennessy, Moët & Chandon, Dom Pérignon and others. As part of the LVMH group, Moët Hennessy combines deep craftsmanship and brand heritage with international distribution and an increasing focus on data-driven decision making across Sales, Marketing and Hospitality.
Moët Hennessy — Data Project Assistant (Alternance) in Paris/Levallois-Perret. Apprenticeship starting Sept 2026 supporting Data & BI on GCP and Power BI.
Role & Responsibilities
- Contribute to the end-to-end data lifecycle: specification, testing and deployment of datasets into the production data warehouse.
- Verify data quality and coherence, propose and implement improvements to stabilize data flows and reporting.
- Design, evolve and document Power BI reports and associated metrics (including DAX/Power Query where applicable).
- Perform operational analyses and produce simple, actionable insights to support business teams’ decision-making.
- Monitor production pipelines and reports; qualify incidents, follow tickets and escalate to data engineers when required.
- Support end users on report usage and runbooks; maintain project documentation in Confluence and metadata in Data Galaxy.
- Participate in Agile rituals and collaborate with cross-functional teams (data engineers, data viz, data scientists and business stakeholders).
Qualifications
- Enrolled in or completing a Bac+4/5 programme in data, business intelligence, information systems, statistics or equivalent.
- Solid knowledge of SQL and fundamentals of data modelling.
- Proficient with Power BI; familiarity with DAX and Power Query is an advantage.
- Good understanding of data workflows and ETL/ELT logic; familiarity with cloud data environments is a plus.
- Working knowledge of Excel; Python is beneficial but not mandatory.
- Strong organisational rigour, autonomy, curiosity and the ability to document and explain technical topics clearly.
- Good level of English, written and spoken, is a plus.
Skills
Experience
Entry-level role suitable for candidates with academic training in data; a first internship, alternance or project experience in data or BI is advantageous but not mandatory.
Education
Bac+4/5 in data, business intelligence, information systems, statistics or equivalent.
Workplace
This position is based in Paris, Île-de-France, France.
Culture
Moët Hennessy blends the heritage and craftsmanship of celebrated maisons with a modern, international working environment; teams are collaborative, high-expectation and oriented toward quality. The data organisation operates in a matrix structure, offering exposure to both global initiatives and maison-specific projects.
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 Moët Hennessy, 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 Project Coordinator (Apprenticeship)», «Data Reporting Apprentice», «Junior Data Analyst (Apprenticeship)», «Business Intelligence Apprentice», and other variations. Our sophisticated search architecture anticipates these variations, ensuring that inquiries using related terms will seamlessly yield the exact roles you desire.