Born of a simple gesture in 1976 , L’Occitane en Provence reveals the living power of flora, where the light of the sun meets the richness of the earth.
With advanced expertise, we turn these natural treasures into sensorial, efficient experiences, as sustainable as possible and profoundly inspired by Haute Provencal nature.
Our culture is built through everyday moments, how we behave, make decisions and show up for each other.
With Trust as our foundation, Curiosity as our compass, Excellence as our standard, we create lasting Impact for the people around us and our planet. Job Summary
The Customer Data Analyst owns and strengthens the technical foundation supporting customer analytics across L’OCCITANE North America. The role combines hands-on data development, automation and customer analytics to deliver reliable datasets, workflows, integrations and reporting solutions that improve commercial performance and the customer experience.
This is more than a reporting role. The successful candidate will use strong technical judgment to create simple, reliable and maintainable solutions; enable business users to answer recurring questions through trusted self-service tools; and apply emerging automation and AI capabilities where they create practical business value.
The role partners closely with CRM, E-commerce, Retail, Customer Care and other teams. It requires curiosity, independent problem solving and proactive communication of progress, risks, dependencies and business impact. The right person translates technical work into clear language and turns new ideas into useful, scalable capabilities without introducing unnecessary complexity. Key Responsibilities
Customer & Commercial Analytics
Conduct deeper analysis when questions require advanced data manipulation, specialized customer-data knowledge or cross-channel interpretation, and provide teams with actionable customer intelligence.
Translate complex findings into clear business implications, recommendations and actions, not simply reports.
Identify meaningful trends, anomalies and opportunities while keeping the focus on decisions and measurable business value.
Support customer segmentation, CRM targeting, lifecycle analysis and customer-behavior analysis across channels and markets.
Validate analytical outputs for accuracy, consistency and appropriate use of customer information.
Data Development, Automation & Reliability
Build, maintain and improve customer-data pipelines, transformations and automated workflows using SQL, Python and appropriate workflow tools.
Develop reusable, well-structured datasets in Snowflake or comparable cloud data platforms for analytics, CRM and reporting use cases.
Integrate internal and external data through APIs, JSON, SFTP, scheduled files and other appropriate methods.
Monitor production processes and proactively resolve failures, data-quality issues and upstream or downstream dependencies.
Design for maintainability by reusing existing assets where practical, avoiding unnecessary tables or pipelines, and documenting technical decisions and support requirements.
Partner with Technology/IT and central teams on data access, infrastructure, security and platform dependencies.
Simplification, Automation & AI
Identify repetitive, manual or low-value activities and challenge whether they should continue in their current form.
Apply a simplify-first mindset by removing unnecessary steps and complexity before automating work.
Design reusable workflows and automation that make recurring analysis faster, more reliable and easier to maintain.
Explore and responsibly apply AI capabilities to customer analytics, segmentation, Voice-of-Customer analysis, reporting and other relevant business problems.
Experiment with new technologies, evaluate their usefulness and turn successful experiments into practical capabilities that can benefit the broader organization.
Reporting, Data & Analytics Capabilities
Develop and maintain trusted semantic models,…