Data Product Manager - Core Data Product (f/m/d)

Worldwide | Sept. 21, 2026

Report as Closed

Company: Decathlontechnology

Country: Worldwide

Type: Onsite

Employment: Full-time

Description:

Our Core Data Product team, within the Data CoE (data center of expertise), is looking for a Data Product Manager in Paris

DECATHLON is accelerating its transformation to become THE global digital sports platform. Digital and AI are the drivers of our 2026-2030 ambition to make sport sustainably accessible. At the heart of this strategy, data is our most critical asset. Our challenge? Make it accessible, trustworthy and actionable in order to be able to make it available to business and strategy

YOUR FUTURE CONTRIBUTION

You will be responsible for defining the vision and roadmap for a Data product, by indirectly supervising a team of data engineers. Your mission will be to make data easy to access and trust in order to support the business in making data-oriented decisions!

Your main missions:

1. Data Product Strategy and Vision
   Definition of the Roadmap: Design and manage the roadmap for data products (algorithms, dashboards, data APIs, AI platforms).

Business Alignment: Ensure that data initiatives meet the company's strategic objectives (e.g. churn reduction via machine learning, price optimization, etc.).

Identification of opportunities: Detect use cases where data can create a competitive advantage or improve internal efficiency.

1. Data Lifecycle Management
   Collection and Infrastructure: Collaborate with Data Engineers to ensure data pipelines are robust and sources are reliable.

Governance and Quality: Guarantee that data is clean, consistent and compliant with regulations (GDPR). He is the guarantor of the “truth” of the data disseminated.

Democratization: Make data accessible and understandable for non-technical users across the organization.

1. Transversal Collaboration
   Technical Interface: Translate business needs into technical specifications for Data Scientists and Data Engineers.

Support for Stakeholders: Educate decision-makers (Marketing, Sales, Management) on the potential and limits of data.

Agility: Manage the development of data models in agile mode (sprints, A/B tests, rapid iterations).

1. Analysis and Measurement of Performance
   Definition of KPIs: Establish success indicators not only for the final product, but also for the performance of the models (precision, recall, data latency).

Impact analysis: Concretely measure the return on investment (ROI) of the data projects implemented.

1. Ethics and Security
   AI ethics: Ensure that the algorithms developed are not biased and respect the ethics of the company.

Security: Ensuring that access to sensitive data is secure and controlled.

TECHNICAL SKILL

Data Product Strategy & Management
Data Governance & Compliance
Business Modeling
Data Architecture
Agile Methodologies
Backlog Management
SQL, Python (for data validation & automation)
Visualization Tools (Tableau, Looker, Power BI, etc.)
AI/ML Integration and ability to manage predictive models.
Data Governance frameworks and compliance knowledge (GDPR, CCPA).
Real-Time Data Integration (APIs, Kafka, Streaming).
Data Modeling, Business Intelligence Tools (Tableau, Power BI).
SQL, Python, and familiarity with data platforms like Databricks and Snowflake.

WHAT YOU BRING

Your latest experiences have allowed you to develop a major interest in issues related to the cloud and data, while consolidating your knowledge of product life cycle (PLM).

• You have at least 3 to 5 years of experience in Product Management in an international context

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