In today's digital landscape, enterprise data is a strategic asset and a digital product; its accuracy, consistency, and timeliness are vital for operational excellence and the success of our GenAI and Large Language Model (LLM) initiatives. Having invested heavily in a robust, multi-year portfolio of data quality rules and profiling solutions, the organization requires continuous optimization of these rules to match evolving business needs. The Data Quality Portfolio Manager exists to strategically manage this global portfolio of solutions, ensuring seamless governance, driving mass cleansing, and partnering across regions and segments to deliver superior enterprise data quality.

What will be your key responsibilities?

Global Portfolio Strategy & Rule Management

• Govern Global DQ Portfolio: Direct and sustain the portfolio of global, regional, and segment-specific Data Quality (DQ) rules through close collaboration with Data Councils, Regional Stewards, and Data Champions.

• Translate Standards to Rules: Work hand-in-hand with Global Data Councils to translate global and segment-specific data standards into active, systemic Data Quality rules.

• Champion Global Tools: Actively influence and support the adoption of a unified global set of tools, frameworks, and processes to implement and scale data quality across the enterprise.

KPI Collaboration & Governance

• Establish Shared KPIs: Partner and collaborate with Global Data Councils, Business Process Owners, and MDM Service Managers to align on and agree to key performance indicators (KPIs) for data health.

• Manage KPI Development & Tracking: Take accountability for managing the technical development, deployment, and regular monitoring of agreed-upon KPIs to provide a clear, transparent view of data compliance.

• Enforce Data Health Standards: Reinforce compliance with agreed KPIs in partnership with Regional Stewards and local business/operating units to drive data discipline.

Collaboration & Operational Capacity Planning

• Sustain Efficient Operations: Collaborate with MDM Service Managers to establish priorities, run efficient day-to-day DQ operations, and secure forward-looking capacity planning for major Segment, Regional, and Global MDM initiatives.

• Shape Technology Roadmap: Partner with Technology Leads to define and communicate functional requirements for the continuous improvement of existing and deployment of future data quality systems.

Data Cleansing & Continuous Improvement

• Drive Mass Cleansing: Partner with Regional Stewards to identify, prioritize, and execute targeted mass data-cleansing activities.

• Promote "First Time Right" Culture: Identify and drive Continuous Improvement Processes (CIP) and "First Time Right" (FTR) data entry opportunities within the regions to prevent data debt at the source.

Qualifications                                                    

• Has a minimum of 10-12 years of experience in Master Data Management and/or Data Quality initiatives spanning multiple data domains in a complex multi-national corporate environment.

• Sound understanding of Data Quality dimensions, Data and Technical Lineage concepts.

• Proven experience of delivering solutions using ML/AI technologies

• Proven track record of delivering user-facing data monitoring and cleansing applications/solutions.

• Considerable experience with SAP Data Services and Information Steward or similar ETL and Data Quality Engines

• Considerable experience with SAP Data Models and understanding of SAP Integration options

• Ability to explain complex technology concepts using common language

• Proven experience in managing Partner resources and technology projects

• Fluent in spoken and written English; any additional language is an advantage

• Bachelor’s degree in business or similar

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