Revenue Data Management Specialist

at  CAPGEMINI ENGINEERING

Role title: Revenue Data Management Specialist
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unluck the value of technology and build a more sustainable, more inclusive world.

REQUIRED SKILLS

• Validate financial transactions, monitor fraud patterns, and maintain data integrity.
• Identify data sources, data flows, and data dependencies to make informed decisions about data management.
• Partner with the business to identify critical revenue data elements for metadata and lineage perspectives for consumption by Data Catalog and Data Quality tracks.
• Assist data consumers in interpreting data correctly, providing context, explaining data nuances, and addressing queries to foster data literacy.
• Define additional standard data validation rules and data validation rules for the data quality engine.
• Perform data quality analysis and validation for sources in scope.
• Incentivize collaboration between revenue management and data teams.
• Create data quality dimension guidelines as a basis for the data quality engine.
• Document data quality issues and collaborate with teams to determine remediation paths to solve them.
• Collaborate with different teams and departments within the organization, acting as a bridge between business users, data analysts, and IT teams to ensure effective communication and understanding of data requirements.
• Utilize strong data analytics skills for data profiling to train the model.
• English C1.

This service encompasses the following activities:

• Validate financial transactions, monitor fraud patterns, and maintain data integrity.
• Identify data sources, data flows, and data dependencies to make informed decisions about data management.
• Partner with the business to identify critical revenue data elements for metadata and lineage perspectives for consumption by Data Catalog and Data Quality tracks.
• Assist data consumers in interpreting data correctly, providing context, explaining data nuances, and addressing queries to foster data literacy.
• Define additional standard data validation rules and data validation rules for the data quality engine.
• Perform data quality analysis and validation for sources in scope.
• Incentivize collaboration between revenue management and data teams.
• Create data quality dimension guidelines as a basis for the data quality engine.
• Document data quality issues and collaborate with teams to determine remediation paths to solve them.
• Collaborate with different teams and departments within the organization, acting as a bridge between business users, data analysts, and IT teams to ensure effective communication and understanding of data requirements.
• Utilize strong data analytics skills for data profiling to train the model.