Profisee - MDM Architect

Job description

Job Description Experience • 7+ years of overall experience in data management, MDM, data architecture • 5+ years of hands-on Master Data Management experience • Strong hands-on experience with Profisee MDM is mandatory • Prior experience reviewing, troubleshooting, stabilising or optimising an existing Profisee implementation is highly desirable Required Technical Experience Mandatory: • Hands-on Profisee implementation experience • Experience configuring and troubleshooting Profisee • Strong understanding of Profisee architecture and implementation patterns • Experience with Profisee data models, matching, merging, survivorship and workflows • Experience analysing Profisee integrations and downstream data flows • Strong understanding of MDM data quality and governance • Experience working with complex enterprise integration landscapes Desirable: • Azure / Microsoft Fabric / Microsoft Purview experience • Experience with APIs and integration platforms • Experience with ERP/CRM environments such as SAP, Salesforce, Oracle or similar • Experience with data stewardship and operating-model design • Experience conducting MDM health checks, architecture reviews or implementation assessments Key Responsibilities The successful candidate will: 1. Current-State Assessment • Review the existing Profisee implementation, architecture and configuration • Understand the current MDM operating model, business processes and ownership • Document key challenges, impacted business processes and manual workarounds • Review how master data is created, changed, approved, mastered and distributed • Assess the current roles and responsibilities across business, data stewardship, technology and support teams 2. Profisee Implementation Review • Assess whether the Profisee implementation is appropriately designed for the organisation's business requirements • Identify areas of unnecessary complexity, over-engineering or configuration that may be contributing to operational issues • Review Profisee data models, entities, attributes, relationships and hierarchies • Review matching, merging and survivorship configuration • Review workflows, stewardship processes, validation rules and business rules • Assess whether configuration follows Profisee implementation best practices • Identify configuration/design issues that may impact data quality or downstream processing 3. Integration & Data Flow Review • Review the end-to-end integration architecture surrounding Profisee • Trace critical data flows from source systems through Profisee to downstream applications • Investigate issues associated with incorrect or unexpected data updates reaching downstream systems • Assess interfaces, APIs, integration services, event/batch mechanisms and transformation logic • Identify potential issues around data ownership, change propagation, sequencing, dependencies and error handling • Assess monitoring, reconciliation, exception handling and support processes • Recommend improvements to integration patterns and controls 4. Data Migration & Data Quality Assessment • Assess the approach used to migrate data into Profisee • Evaluate the organisation's confidence in migrated master data • Identify gaps in reconciliation, validation and data-quality controls • Review DQ rules, thresholds and validation logic • Assess whether current DQ controls are overly restrictive or generating unnecessary operational effort • Recommend a pragmatic approach to balancing data quality, business usability and operational efficiency