Data Quality & MDM Manager (M/F)

NEW NET 3DGirondeEURESpublished 09/18/2026
Must-have:VueDataAI
Machine translation — original language: French.Show original

Job Description:

As an organizer of recruitment forums, Talents Handicap accompanies many companies & organizations in France in their recruitment of employees with disabilities. Currently participating in one of our forums. The company LECTRA is currently looking for profiles. As a Data Quality Manager, you will guarantee the quality, consistency, and governance of master data across the GTM (Go-to-market) ecosystem, enabling a reliable Customer 360 view to serve business processes, reporting, and AI use cases.

Missions***Define data quality rules and ensure their monitoring

  • Establish and maintain master data standards
  • Drive data cleansing and enrichment
  • Implement data governance processes
  • Ensure the resolution of data incidents
  • Work in close collaboration with Data Stewards, particularly on the RevOps side, in order to co-define, deploy, and enforce master data quality and governance rules in connection with business uses.

Profile

With a Master's degree (Bac+5), you have at least 4 years of experience in data quality and master data management (MDM), ideally within a GTM / CRM ecosystem. You have a good understanding of the GTM / Customer 360 data model and master data quality frameworks and tools. Possessing an analytical mind and a real troubleshooting capacity, you know how to coordinate Business, IT, and Data stakeholders.

REQUIRED SKILLS

  • Data governance and MDM (Master Data Management Frameworks and data quality tools.
  • Good understanding of the GTM / Customer 360 data model.
  • Fluent English (international environment) Analytical mind and troubleshooting capacity.
  • Understanding of AI challenges applied to data (preparation, quality, exploitation of data for AI use cases / advanced analytics)

DESIRED SKILLS

  • Inter-team coordination (Business / IT / Data) Ability to collaborate with Data/AI teams (Data Engineers, Data Scientists, AI Engineers) to align data quality with AI use cases