Master Data Quality Coordinator

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Job Description

Takeda Business Solutions (TBS) is a global function within Takeda with the objective of enabling Takeda’s business strategy, delivering innovative simplified solutions and cost reduction, improving service and providing a transformation engine for continuous improvement for Takeda.

‘Building and Delivering Simplified and Innovative Solutions’ is our overarching vision with Patients at the center of all that we do. MDM CoE is the expert arm of Takeda MDM Organization, leading development of Best in Class Processes, owning the global MDM Governance and driving Data Quality analytics. MDM CoE cooperates closely with the MDM Operations, which is responsible for the transactional area of MDM as well as Global Manufacturing Services, Finance, Commercial, Supply Chain and Data, Digital & Technology functions.
 

Reporting to the MDM Global Process Expert, with the dotted line to the Head of Supply Chain Master Data Governance, the Master Data Quality Coordinator will be responsible for next-generation data quality solutions and for ensuring highest data quality standards to allow the business operations to smoothly deliver life-saving pharmaceutical products to patient in need and prepare the organization for the transition to SAP S4 HANA.
 

INSPIRED BY PATIENTS. POWERED BY YOU.

Accelerate value & make an impact by:

• Building advanced Supply Chain master data quality solutions by extracting, transforming, and visualizing data quality issues using dimensional modeling and programming.
• Leading complex master data cleansing initiatives to improve consistency across core systems, partnering closely with Global Manufacturing and Supply Chain stakeholders.
• Serving as the Global Master Data Quality Champion, promoting a “first-time-right” culture and educating the organization on the cost and impact of poor data quality.
• Designing and implementing global master data quality processes to ensure transactions are posted to the correct master data, in the right place and at the right time.
• Analyzing, enriching, and improving large-scale datasets by executing complex remediation activities, including mass-load updates across millions of enterprise records.
• Designing and automating data quality checks in MDG in collaboration with the ERP/MDG team to reduce human error and mitigating lifecycle data risks.
• Developing and maintaining Qlik-Sense dashboards and SQL-based back-end transformations to monitor and improve data quality at scale.
• Maintaining and optimizing MDC workflows (monitoring, troubleshooting, and implementing enhancements) to support business processes and data governance requirements.
• Applying data governance standards and partnering with the GMS Supply Chain Data and MDM CoE team to develop and refine business rules.
• Collaborating with cross-functional business units and functions to prioritize information needs, defining improved processes, and identifying new opportunities to enhance data quality.
• Acting as a change agent and master data quality ambassador by driving awareness and supporting stakeholder adoption of data quality best practices.
• Representing master data quality expertise in global projects and transformation programs.
   

Required qualifications:

• At least 4 years of experience with Master Data processes and SAP Master Data Model architecture.
• At least basic working knowledge of SQL.
• Experience with reporting and analytics tools, especially Qlik.
• Strong analytical skills applied to a wide range of business challenges.
• Strong communication and interpersonal skills, with proven ability to collaborate with stakeholders across functions and geographies.
• Ability to build trusted relationships by consistently delivering on commitments.
• Ability to drive change in a developing environment and constructively challenge existing ways of working.
• Continuous improvement mindset.
• Communicative level of English.
   

Preferred qualifications:

• Bachelor’s degree in mathematics, economics, computer science, information management, statistics, or a related field.
• Exposure to digital innovation and auto