Principal Architect - IT, Data Quality & MDM

As a Principal Architect - IT, Data Quality & MDM at MKS, you will play a crucial role in improving master data quality across various data domains by partnering with business stakeholders from divisions like Global Supply Chain, Global Ops, Sales, Service, and Finance. Your responsibilities will include architecting, designing, and implementing solutions using Master Data Management platform and tools to establish a single source of truth, implement data quality frameworks, and enable real-time integration and automation supported by CI/CD-driven deployment models. Your key responsibilities will include: - Developing and executing a comprehensive data cleansing approach aligned with industry best practices - Implementing data quality monitoring and governance processes and tools - Automating validation and remediation workflows using CAI - Designing integration workflows for automated data quality checks across source and target systems - Leveraging event-driven and API-based integrations for real-time validation of master data - Implementing rule engines for intelligent data cleansing, anomaly detection, and auto-remediation - Orchestrating workflows for bulk and incremental data corrections using integration pipelines - Designing and implementing End-to-End Master Data Management architectures and solutions for Vendor, Customer, Items, etc. - Ensuring master data is established as a single source of truth across IT systems by integrating master data from the MDM system - Building scalable integration frameworks between MDM, ERP, CRM, and downstream applications - Implementing real-time and batch data synchronization using integration platforms - Using API management and microservices-based integration patterns for master data consumption - Enabling intelligent data exchange mapping, transformation, and schema alignment - Working with stakeholders to profile data quality of critical data elements and create data quality scorecards - Developing and implementing data cleansing rules and data de-duplication techniques - Researching third-party reference data sources and integrating data quality management - Enhancing data quality processes using CAI capabilities Your qualifications should include: - 3+ years of recent experience implementing enterprise Master Data Management Solutions using Informatica MDM Cloud platform - 15+ years of hands-on experience in data & analytics project implementations with proficiency in Data Quality and MDM implementation approaches - Strong database skills and proficiency in SQL and data analysis Additionally, you will provide guidance and training to stakeholders and cross-functional team members on data quality best practices, foster a culture of data quality awareness, maintain detailed documentation, produce reports and recommendations, and drive continuous improvement in IT and Data Quality/MDM solutions. In summary, as a Principal Architect at MKS, you will play a critical role in improving master data quality, implementing data quality frameworks, and enabling real-time integration and automation, leveraging your expertise in Informatica MDM Cloud platform and tools. As a Principal Architect - IT, Data Quality & MDM at MKS, you will play a crucial role in improving master data quality across various data domains by partnering with business stakeholders from divisions like Global Supply Chain, Global Ops, Sales, Service, and Finance. Your responsibilities will include architecting, designing, and implementing solutions using Master Data Management platform and tools to establish a single source of truth, implement data quality frameworks, and enable real-time integration and automation supported by CI/CD-driven deployment models. Your key responsibilities will include: - Developing and executing a comprehensive data cleansing approach aligned with industry best practices - Implementing data quality monitoring and governance processes and tools - Automating validation and remediation workflows using CAI - Designing integration workflows for automated data quality checks across source and target systems - Leveraging event-driven and API-based integrations for real-time validation of master data - Implementing rule engines for intelligent data cleansing, anomaly detection, and auto-remediation - Orchestrating workflows for bulk and incremental data corrections using integration pipelines - Designing and implementing End-to-End Master Data Management architectures and solutions for Vendor, Customer, Items, etc. - Ensuring master data is established as a single source of truth across IT systems by integrating master data from the MDM system - Building scalable integration frameworks between MDM, ERP, CRM, and downstream applications - Implementing real-time and batch data synchronization using integration platforms - Using API management and microservices-based integration patterns for master data consumption - Enabling intelligent data exchange mapping, transformation,