For more than a century, L’Oréal has devoted its energy, innovation, and scientific excellence solely to one business: Beauty. Our goal is to offer every person around the world the best of beauty in terms of quality, efficacy, safety, sincerity and responsibility to satisfy all beauty needs and desires in their infinite diversity. 

At L'Oréal, our IT teams design and build solutions to ensure high performance for all our business sectors by imagining new ways of doing things, from designing websites to building algorithms and predicting new trends. They can be found leading teams towards a more connected and digitalized future in IT retail, e-commerce, CRM, data, AI, cybersecurity, Cloud and E-Marketing. You never stop learning at L'Oréal IT because things change at the speed of light! Come join our dynamic team!

About the Role: Impact and Expectations

The Data Analyst at L'Oréal is much more than a report builder; you are a Data Architect and Strategist. Your role is to ensure that the vast amounts of data we generate are organized, consistent, and perfectly aligned with our business goals.

You will be expected to:

• Be the Translator: Act as the vital link between business stakeholders and technical developers, ensuring that business rules are accurately reflected in our data structures.
• Champion Data Integrity: Own the end-to-end traceability of data, ensuring that from the moment data is born to the moment it is visualized, it remains accurate and trustworthy.
• Architect for Growth: Design scalable schemas that don't just solve today's problems but are ready for the AI and automation challenges of tomorrow.
• Foster a Data Culture: Drive excellence in documentation and modeling best practices, making our data ecosystem accessible and understandable for everyone.

Key Responsibilities: What You Will Do

In this role, you will be the custodian of our data logic. 

Your main objectives include:

• Advanced Data Modeling: Design and maintain sophisticated data structures (Conceptual, Logical, and Physical). You will lead the implementation of Star and Snowflake schemas, applying normalization or denormalization strategies as needed.
• Consistency & Traceability: Build and manage the lineage between raw, curated, and semantic layers. You will define primary/foreign key relationships and cardinality to ensure absolute referential integrity.
• Requirement Transformation: Turn complex business needs into structured technical models. You will be responsible for clearly documenting transformation logic, field definitions, and data relationships.
• Quality Assurance: Validate data across all layers using SQL-based checks and rule-based testing. You will define the granularities and hierarchies that power our global analytics.
• Performance Optimization: Partner with the development team to suggest and apply table optimization strategies—such as indexing, partitioning, and clustering—within BigQuery to ensure lightning-fast queries.
• Collaborative Integration: Support Product and Engineering teams with your business domain expertise, evaluating new data sources and enforcing logic for data unification and version control.

What We Are Looking For

We need a detail-oriented professional who loves "connecting the dots" and thrives in a collaborative, tech-forward environment.

Education & Experience:

• Proven Track Record: 4–6 years of experience in data-related roles.
• Specialization: Ideally, 2–3 years specifically focused on data modeling, data validation, or business logic structuring.
• Education: Bachelor’s degree in Computer Science, Information Systems, Mathematics, or a related field.

Technical Knowledge & Tools:

• SQL Mastery: Advanced SQL proficiency is a must. You should be able to write highly optimized queries and interpret execution plans with ease.
• Cloud Data Warehousing: Deep experience with BigQuery or other columnar databases.
• Modeling & Transformation: Expertise in dbt, Power BI Data Modeling, or LookML.
• Visual Documentation: Proficiency in tools like Lucidchart or other process mapping software to visualize data flows.
• Documentation Platforms: Experience using Confluence or dbt docs to maintain a "single source of truth" for data logic.

Skills & Competencies:

• Analytical Rigor: A strong ability to handle ambiguity and evolve logic as business needs change.
• Strategic Communication: Excellent documentation skills and the ability to explain complex technical designs to non-technical stakeholders.
• Quality First: A mindset focused on UAT (User Acceptance Testing) and the development of rigorous test cases for data pipelines.
• Collaboration: A true team player who enjoys working across diverse tech and functional teams.

Don’t meet every single requirement? At L'Oréal, we are dedicated to building a diverse, inclusive, and innovative workplace. If you’re excited about this role but your past experience doesn’t align perfectly with the qualifications listed in the job description, we encourage you to apply anyways! You may just be the right candidate for this or other roles!

We are an Equal Opportunity Employer and take pride in a diverse environment. We would love to find out more about you as a candidate and do not discriminate in recruitment, hiring, training, promotion, or other employment practices for reasons of race, color, religion, gender, sexual orientation, national origin, age, marital or veteran status, medical condition or disability, or any other legally protected status.