Priniciple MDM Architect

Overview

Lead the enterprise data architecture strategy and Master Data Management (MDM) initiatives, including AI-enabled MDM, data governance and stewardship, and integration across enterprise applications. Serve as the lead SME and architect for MDM solutions and lead a team of architects, developers, analysts, and data engineers.

What you'll do

• Define and lead enterprise-wide data architecture strategy and roadmap.
• Establish scalable architecture for Master Data Management, Data Governance, Data Quality, Metadata Management, and Reference Data Management.
• Develop target-state data architecture aligned with business objectives and digital transformation initiatives.
• Provide architectural leadership and governance across data platforms, integrations, and downstream applications.
• Define architecture standards, design principles, and best practices for enterprise data management.
• Define and implement an AI-driven MDM strategy to improve master data quality, governance, and operational efficiency.
• Evaluate and integrate Generative AI, Machine Learning, and Intelligent Automation capabilities into MDM processes.
• Design AI-assisted data stewardship workflows that reduce manual effort in data validation, enrichment, classification, and exception handling.
• Leverage AI models for intelligent entity resolution, duplicate detection, survivorship optimization, and record matching across customer, product, supplier, and vendor domains.
• Establish AI governance policies to ensure transparency, explainability, security, and regulatory compliance of AI-driven data management processes.
• Serve as the organization's lead SME and architect for MDM solutions.
• Design and implement Customer, Product, Vendor, Supplier, and Reference Data Master solutions.
• Establish and maintain a "Single Source of Truth" and Golden Record strategy.
• Define survivorship, matching, merging, hierarchy management, and data stewardship processes.
• Lead MDM platform selection, evaluation, implementation, and optimization initiatives.
• Ensure MDM solutions support operational, analytical, and regulatory requirements.
• Define enterprise data governance frameworks, standards, policies, and operating models.
• Partner with business stakeholders to establish data ownership, stewardship, and accountability models.
• Lead data quality initiatives including profiling, monitoring, remediation, and continuous improvement.
• Implement governance processes to ensure data consistency, accuracy, compliance, and auditability.
• Drive adoption of data governance practices across business units.
• Partner with business and data stewards to implement GenAI-powered capabilities for data issue identification and remediation recommendations, automated business rule generation and validation, natural language search and query across master data domains, metadata documentation and data catalog enrichment, and AI-assisted onboarding of new data sources and domains.
• Design end-to-end data integration architectures across ERP, CRM, PLM, supply chain, and analytics platforms.
• Lead integration strategy between MDM and enterprise applications.
• Collaborate with application teams to define data exchange patterns, APIs, services, and event-driven architectures.
• Review and approve technical solution designs for strategic enterprise initiatives.
• Evaluate emerging data technologies, platforms, and industry trends.
• Establish enterprise standards for data architecture and implementation.
• Conduct architecture reviews and provide technical oversight for all MDM initiatives.
• Drive innovation while balancing scalability, maintainability, and operational support requirements.
• Partner with executive leadership, business stakeholders, data stewards, and technology teams.
• Translate business requirements into scalable architectural solutions.
• Present architecture roadmaps and recommendations to senior leadership.
• Serve as escalation point for critical data and architecture issues.
• Lead and mentor architects, developers, analysts, and data engineers.
• Establish technical standards and review processes.
• Support project planning, estimation, resource allocation, and delivery governance.
• Foster a culture of engineering excellence and continuous learning.

What you'll need

• 15+ years of experience in Data Management, Data Architecture, Data Integration, or related disciplines.
• 8+ years of experience designing and implementing enterprise MDM solutions.
• Proven experience leading large-scale enterprise data transformation initiatives.
• Experience defining MDM strategy and enterprise data roadmaps.
• Experience managing architecture teams and cross-functional delivery organizations.
• Experience working directly with executive stakeholders and business leaders.
• Strong experience in one or more of the following platforms: Tibco EBX (Orchestra Networks), SAP MDG.
• Expertise in Data Governance frameworks and operating models.
• Experience implementing Data Stewardship programs.
• Strong understanding of metadata management and reference data management.
• Experience with data quality assessment, profiling, remediation, and monitoring.
• Knowledge of regulatory and validation environments.
• Experience integrating with enterprise platforms such as SAP ERP, Microsoft Dynamics 365, Salesforce (SFDC), PLM Solutions, CRM Platforms, Supply Chain Systems, and Data Warehouses and Analytics Platforms.
• Integration experience with APIs, SOAP Services, REST Services, ETL/ELT Platforms, and Enterprise Integration Platforms (Boomi, MuleSoft, etc.).
• Experience deploying enterprise data platforms in AWS, Azure, or GCP.
• Knowledge of Redshift, PostgreSQL, Oracle, SQL Server, or equivalent databases.
• Experience with high availability, disaster recovery, and resiliency architectures.
• Experience with WebLogic, JBoss, Tomcat, or similar middleware platforms.

Nice to have

• Experience in Life Sciences, Healthcare, Pharmaceutical, Manufacturing, or Consumer Products industries.
• Experience integrating with Dun & Bradstreet (D&B) services for identity resolution and enrichment.
• Experience 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.

Details

• Location: India - Remote.