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India
Remote only
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Principal MDM Architect based in India.
The Principal MDM Architect will define and lead the enterprise-wide Master Data Management (MDM) strategy, building scalable data architecture that supports business transformation and operational excellence. This senior leadership role will drive the design and implementation of data governance, data quality, metadata management and reference data solutions across multiple business domains. A key focus will be integrating Artificial Intelligence, Machine Learning and intelligent automation into MDM processes to improve data accuracy, efficiency and decision-making. The successful candidate will establish trusted data foundations, including single sources of truth and golden records, while ensuring seamless integration across enterprise platforms. Working closely with executive stakeholders, business leaders and technical teams, this role will shape architectural standards, guide strategic initiatives and mentor multidisciplinary teams in a complex enterprise environment.
Define and lead the enterprise data architecture strategy and roadmap, ensuring alignment with business objectives and digital transformation priorities.
Establish scalable architecture frameworks for Master Data Management, Data Governance, Data Quality, Metadata Management and Reference Data Management.
Develop target-state data architecture, architectural standards, design principles and implementation best practices.
Lead the organisation's MDM strategy and serve as the primary subject matter expert and architect for enterprise MDM solutions.
Design and implement master data solutions across customer, product, vendor, supplier and reference data domains.
Establish single-source-of-truth and golden-record strategies, defining matching, merging, survivorship, hierarchy management and data stewardship processes.
Lead MDM platform evaluation, selection, implementation and optimisation initiatives.
Define and implement AI-driven MDM capabilities using Generative AI, Machine Learning and intelligent automation to improve data quality and operational efficiency.
Design AI-assisted data stewardship workflows for data validation, enrichment, classification, exception handling and remediation.
Apply AI models to entity resolution, duplicate detection, record matching and survivorship optimisation across master data domains.
Establish AI governance policies that support transparency, explainability, security and regulatory compliance.
Develop enterprise data governance frameworks, policies, standards and operating models, working with business stakeholders to establish data ownership and accountability.
Lead data quality initiatives, including profiling, monitoring, remediation and continuous improvement, ensuring data consistency, accuracy and auditability.
Promote the adoption of data governance and stewardship practices across business units.
Collaborate with business and data stewards to implement GenAI-powered capabilities for identifying data issues, generating business rules, enabling natural language queries, enriching metadata and onboarding new data sources.
Design end-to-end integration architectures across ERP, CRM, PLM, supply chain and analytics platforms.
Define integration strategies, APIs, services, data exchange patterns and event-driven architectures in collaboration with application teams.
Review and approve technical solution designs for strategic enterprise initiatives, providing architectural oversight across MDM projects.
Evaluate emerging data technologies and industry trends, establishing standards that balance innovation, scalability, maintainability and operational support.
Partner with executive leadership, business stakeholders, data stewards and technology teams to translate business requirements into scalable architectural solutions.
Present architecture roadmaps and recommendations to senior leadership and act as an escalation point for critical data and architecture issues.
Lead and mentor architects, developers, analysts and data engineers, supporting technical standards, project planning, resource allocation and delivery governance.
15+ years of experience in Data Management, Data Architecture, Data Integration or related disciplines.
At least 8 years of experience designing and implementing enterprise MDM solutions.
Proven experience leading large-scale enterprise data transformation initiatives and defining MDM strategies and enterprise data roadmaps.
Experience managing architecture teams and cross-functional delivery organisations, with a track record of working directly with executive stakeholders and business leaders.
Strong expertise in at least one major MDM platform, such as TIBCO EBX (Orchestra Networks) or SAP MDG.
Extensive knowledge of data governance frameworks, operating models, data stewardship programmes, metadata management and reference data management.
Experience with data quality assessment, profiling, remediation and monitoring, as well as familiarity with regulatory and validated environments.
Strong enterprise integration experience with platforms such as SAP ERP, Microsoft Dynamics 365, Salesforce, PLM solutions, CRM platforms, supply chain systems, data warehouses and analytics platforms.
Practical experience with integration technologies, including APIs, SOAP and REST services, ETL/ELT platforms and enterprise integration solutions such as Boomi or MuleSoft.
Experience deploying enterprise data platforms on cloud environments such as AWS, Azure or Google Cloud Platform.
Knowledge of databases such as Amazon Redshift, PostgreSQL, Oracle, SQL Server or equivalent technologies.
Understanding of high availability, disaster recovery and resilient architecture principles.
Experience with middleware platforms such as WebLogic, JBoss, Tomcat or similar technologies.
Strong strategic thinking and an enterprise-wide perspective, with excellent executive communication and stakeholder management skills.
Ability to influence across business and technology teams, drive organisational adoption of MDM and data governance practices, and make effective decisions in complex environments.
Additional assets:
Experience in Life Sciences, Healthcare, Pharmaceutical, Manufacturing or Consumer Products industries.
Experience integrating Dun & Bradstreet (D&B) services for identity resolution and data enrichment.
Background with large-scale customer data platforms and commercial data ecosystems.
Knowledge of domain-driven architecture and modern data management practices.
Experience supporting validated and regulated environments.
Fully remote working arrangement from India.
Full-time employment.