Customer Data Analyst

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, dashboards, recurring reporting and analytical products using Microsoft Power BI and other appropriate tools.
• Create standardized, reusable data products that reduce repeated manual extracts, recurring reporting and low-value ad hoc requests.
• Help develop Customer 360 and customer-journey views that connect customer behavior across channels and activities.
• Maintain clear documentation of data sources, KPI definitions, transformations, workflow dependencies, validation steps and troubleshooting procedures.
• Assess whether work should be simplified, automated, transferred to self-service or stopped before building a new solution.

Business Partnership & Communication

• Partner with CRM, E-commerce, Retail, Customer Care, Marketing, Finance and technical teams to understand the decision behind a request and translate business needs into practical solutions.
• Proactively communicate status, risks, blockers, dependencies, trade-offs and expected resolution dates so stakeholders are not surprised by gaps or delays.
• Explain technical processes, limitations and recommendations clearly to technical and non-technical audiences.
• Constructively challenge requests when a simpler, more reusable or higher-value approach is available.
• Share knowledge, documentation and reusable solutions so critical processes do not depend on one person.

Experience & Skills

Required

• Strong SQL skills, including complex transformations, joins, data validation, performance troubleshooting and reusable logic.
• Hands-on Python experience for data processing, automation, integration or analytical applications.
• Experience with Snowflake or another modern cloud data warehouse.
• Experience building and supporting data pipelines, automated analytical processes or production workflows.
• Experience working with APIs, JSON and file-based integrations such as SFTP.
• Experience with Microsoft Power BI or a comparable business-intelligence platform, including data modeling and dashboard development.
• Strong debugging and root-cause analysis skills, with the ability to independently own an issue through resolution.
• Clear, proactive written and verbal communication across technical and business teams.
• Sound analytical judgment and the ability to connect technical outputs to customer, commercial or operational decisions.

Preferred

• Experience with customer, CRM, retail, E-commerce, and marketing data.
• Experience with customer segmentation, campaign audiences, triggered communications or customer-journey analysis.
• Experience with KNIME or another low-code workflow and orchestration platform.
• Experience with Git or another version-control tool.
• Familiarity with AI-assisted analytical tools and responsible use of customer data.
• Experience creating self-service data products or analytical applications for business users.

What Will Make You Successful

• Ownership. You independently own the technical work and its operational reliability. You raise issues early, explain the impact and drive resolution.
• Curiosity. You ask why, learn unfamiliar tools and business processes quickly, and investigate what does not make sense.
• Pragmatism. You can build sophisticated solutions, but choose the simplest approach that reliably solves the problem and can be maintained.
• Simplification. You reduce unnecessary steps before automating and challenge work that no longer provides enough value to continue.
• Business orientation. Technology is a means, not the outcome. You measure success through adoption, reliability, efficiency, customer experience and commercial value.
• Communication. You provide context, status and risks frequently enough that partners are not surprised.
• Collaboration. You work transparently across teams, document decisions and build solutions that others can understand and support.

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