Data Architect

Location: Paris

Time Type: Full time

Job Description

About the tech team

Our global Tech team operates in an agile manner within a dynamic product organization. Immerse yourself in a collaborative environment where innovation thrives, and your contributions will play a direct role in shaping the path of our cutting-edge products. As a key player in our agile setup, you'll have the opportunity to enhance efficiency, foster creativity, and play a pivotal role in our product development process. Become part of a team that embraces adaptability and values continuous improvement, ensuring we stay at the forefront of global technology advancements.

Your key missions

Permanent member of the Data Architecture Chapter, you will be operationally integrated within the various data product squads. This squads are teams responsible for delivering different types of data products (Business process, analytics use cases,…) and your mission will be to ensure the design of data architecture fitting the stakeholders needs or product's vision and guarantee an aligned architecture strategy across the organization. Your scope will cover all aspects of data architecture, from data platform tech components or data security to data flows and data modelling design. Additionally, you will be instrumental in shaping the Global Architecture guidelines, the data architecture frameworks and ensuring consistency and high-quality standards.

• Build data architecture frameworks for a specific tech/data product, in compliance with global standards for Pernod Ricard (reference, meta and/or master data, data management procedures...)
• Oversee the continuous improvement of defined frameworks to meet both current and future business needs whilst securing optimal data accuracy & accessibility (based on new data usage uncovered by data scientists...)
• Contribute to the identification of significant data assets for the enterprise & to the translation of business requirements into data products (database, warehouse, stream...)
• Identify & assess potential impacts/opportunities of product choices from a data architecture standpoint (compliance of proposed data models in new applications to be bought, interdependency with other products architecture...)
• Coordinate with other Data/Tech Architects as needed to secure the consistency of architecture decisions within PR
• Promote global enterprise data strategy within the squad
• Provide data architecture best practices & bring forward new ways of thinking around data to improve outcomes
• Participate in transversal data architecture initiatives (market intelligence, cross-product/family initiatives...) as needed, and continuously develop their own skills based on industry trends/enterprise needs

If you recognize yourself in the description below, don’t wait to apply!

• Experience: at least 5 years of professional experience in this area. 
• Technology: Azure, DBT, Databricks, Snowflake, Power BI
• Strong knowledge of conceptual, logical and physical modeling, especially for rationalizing data objects
• Ability to collaborate with an understanding of architecture/integration concept & principles
• Ability to define the value of the data asset to the enterprise
• Experience in advanced programming and administering databases
• Strong communication skills, with the ability to talk with both technical & non-technical stakeholders
• Mastery of data governance & security guidelines
• Agile ways of working (collaboration, CD/CI...)
   

Wait, there’s more…

We offer you an outstanding and collaborative workplace that embodies our sharing & conviviality culture, the possibility to work from home (2 days a week), a very complete mutual insurance, an attractive compensation including profit-sharing, the possibility to train daily, employee events…

Pernod Ricard values diversity and solidarity within its organization and in its relations with stakeholders. Our recruitment methods focus on skills, and we welcome all types of talents.

Job Posting End Date:

Target Hire Date:

2026-04-01

Target End Date: