Fonction professionnelle: Information Systems

Type de poste: Permanent

Type de contrat: Full - Time

Site: FR - Ile De France

Pays: France

Data Product Manager

Performance at the core

L’Oréal 20-50-100 digital strategy is measured through a Digital Performance Cockpit, which outlines performance for the different facets of the business.  100% Love Brand – how the Group is performing on Owned site audiences, Share of organic and paid search, Share of Owned Social, Share of Earned Media.  50% Direct Relationship with Consumers : how we perform in the Precision Advertising space, from the quality of targeting to the ROI of campaigns, the productivity of our Identified Consumers Databases.  20% eCommerce : Growth vs. Market, Direct vs. Indirect growth, Channels performance, Share of e-Merchandising visibility, leading to Market share evolution.

Analytics Performance journey initiated

The first Digital Performance Cockpits have been launched in 2015 and share across the organization with Top 200 Executives exposed.  The Digital Performance team supports 20+ Countries & 20+ Brands for their Top Management visits, with reports production, data analysis and strategic business recommendations. Cockpits automation has been kick-started in 2016, and the next step is to fully automatize the 20-50-100 Digital Performance measurement to allow integration in all business meetings, and allow Digital Performance team to focus on value-added business recommendations and coaching to enhance business performance across the organization, changing mindsets to “Data Driven Decision Making”.

Building the Marketing Data Factory

Digital Cockpit is now opened to 3500 users, targeting 5000 users in 12 months and transitioning from a Digital Cockpit to a Marketing Cockpit in the digital age.

Cockpit is the visible output of a Marketing Data Factory, processing data from raw inputs to business outputs, foundations being a sustainable & scalable platform, ensuring the following steps:

      1) clear assessment of inputs raw data (sourcing / accuracy / quality)

     2) alignment to internal master data management

      3) set up of data injection & sustainability of storage (keep history)

     4) data processing: development & ETL to deliver output datasets (from new sources or thru data crossing of existing sources) for cockpit product & for data science lab

    5) creating output product: data visualization (out of the box & custom developments) adapted to roles & scope, offering self BI capabilities

    6) monitoring tool usage & offering training to drive adoption

Data Factory is co-built by 3 sub-teams within the organization:

  • Cockpit Product team
  • Data Factory Technical team
  • Cockpit Deploy & Run team  


We are recruiting our Cockpit Product Manager to lead the existing Cockpit Product team

Cockpit Product Team management

  • Own or contribute to all steps of the data factory process:
    • 1) OWN - Clear assessment of inputs raw data (sourcing / accuracy / quality) – includes the delivery of the data exchange interface as document providing inputs to Technical team
    • 2) CONTRIBUTE to MDM > define how clean are the inputs regarding our MDM & co-design with technical team how to address disconnects, ensure proper data mapping
    • 3) CONTRIBUTE - Set up of data injection & sustainability of storage  > to be defined with Technical team in the data exchange interface
    • 4) CONTRIBUTE - data processing for output datasets delivery > what KPI, how calculated & where (in data flow or in visualization) to be defined upfront in the data exchange interface with Technical Team
    • 5) OWN - creating output product: data visualization (out of the box & custom developments) adapted to roles & scope,
    • 6) CONTRIBUTE - monitoring tool usage & offering training to drive adoption > While monitoring is owned by Run team, the delivery of training documentation/videos is under the ownership of Product team

  • Be the main interface of Global Business Owners to collect all data regarding business needs for integration of new KPI in the cockpit – both inputs regarding technical aspects & the business expectations in terms of product output (to define what visualization, for who, what history expected etc….) 
  • Monitor backlog & organize team activity (Team: QA specialists/Data viz specialists) based on roadmap priorities / assessment of business inputs readiness
  • Ensure cockpit product data quality & consistency thru complete business QA based on true end users profile
  • Provide needed training documentation & videos for end users. Ensure remote and in class training for local experts (cockpit champions)
  • Engage with key entities to follow up & understand local customization & share with Global team


  • Engineering background
  • Business training is a plus
  • Strong experience of project management / AMOA
  • Data analytics mindset
  • Ability to interface between business experts and technical teams
  • Strong communication & change management skills