Master Data Manager

Experience
7+ years of overall experience in data management / MDM / data architecture
5+ years of hands-on Master Data Management experience
Strong experience with Informatica MDM or another leading MDM platform
Experience assessing MDM architecture, data quality, integration and operating models
Profisee experience is desirable but not mandatory
Required Technical Experience
Mandatory:
Strong experience with Informatica MDM or another enterprise MDM platform
Strong understanding of MDM architecture and implementation patterns
Experience with matching, merging, survivorship and golden-record concepts
Strong understanding of data quality and data governance
Experience reviewing enterprise integration architectures and data flows
Experience with data migration, reconciliation and validation
Experience assessing MDM operating models and stewardship processes
Ability to analyse complex MDM implementations and identify root causes of business/data issues
Desirable:
Profisee experience
Azure / Microsoft Fabric / Microsoft Purview
API and integration architecture
SAP, Salesforce, Oracle or other enterprise source/consumer systems
Experience with MDM health checks or independent implementation reviews
Experience in retail, FMCG, hospitality or multi-site organisations
Key Responsibilities
1. Business & Current-State Assessment
Understand the business processes dependent on master data
Document current challenges, business impacts and manual workarounds
Understand how master data is created, maintained, approved and consumed
Identify key business and technology stakeholders
Assess current data ownership, stewardship and governance arrangements
2. MDM Architecture Assessment
Review the overall MDM architecture and solution design
Assess the alignment between business requirements and the existing MDM implementation
Identify unnecessary complexity, duplication or over-engineering
Assess MDM patterns including - Master data domains, Golden records, Matching and deduplication, Survivorship, Hierarchies, Data stewardship, Data governance
Assess whether the current solution is aligned to MDM best practices
3. Integration & Data Flow Assessment
Review the end-to-end data flow between source systems, MDM and downstream applications
Analyse how master-data changes propagate through the organisation
Identify potential causes of incorrect downstream updates
Review integration patterns, interfaces, APIs, batch processes and event-driven processes
Assess data ownership and system-of-record responsibilities
Review reconciliation, monitoring, error handling and exception-management processes
Identify control gaps contributing to downstream business issues
4. Data Quality & Migration Assessment
Assess the quality and integrity of data migrated into the MDM platform
Review migration methodology, reconciliation and validation controls
Identify potential gaps in data profiling and cleansing
Review DQ rules, thresholds and exception processes
Determine whether current DQ controls are overly restrictive relative to business requirements
Recommend a pragmatic approach to data-quality management
5. MDM Operating Model
Assess the current MDM support and operating model
Review roles and responsibilities across business, IT, data stewards and support teams
Assess governance and decision-making processes
Review incident and problem-management processes
Identify opportunities to improve operational ownership and accountability

Work arrangement
No