Senior Manager, Enterprise Architect
Listed on 2026-08-30
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IT/Tech
Data Engineering, Data Warehousing, Information & Knowledge Management
12 years of experience, may have supervisory or management experience
Must be able to obtain a Public Trust clearance
Provides the technical leadership and direction in implementing enterprise information/data management practices. Responsible for leading and engaging in information/data management projects including the enterprise information architecture, information models and flows, data dictionaries, data standards, and data quality standards and processes. Responsible for developing and maintaining the logical enterprise information architecture that enables seamless information interoperability of systems from transaction systems, document management systems and information delivery systems.
Experienced in developing information architectures aligned information lifecycle management. Experienced performing conceptual, logical, and physical data modeling with data modeling tools and database design in complex, large-scale data environments. Experienced in transactional data modeling, dimensional modeling, and object-oriented modeling. Experienced in developing data models that support, inter alia, time dependency, historical tracings, taxonomies (simple and complex), and multilingual data. Knowledge of application modeling languages/techniques (e.g., UML, OML, entity relationship modeling, DFDs) including the ability to create and read the associated diagrams.
Experienced creating enterprise models incorporating master and reference data. Experience in creation of data dictionaries, defining metadata management approaches and governance processes. Experience in developing and implementing IT architecture plans, enterprise information architecture standard and guidelines, software development methodologies and strategic plans. Experience in developing data sharing standards and architecting scalable service-oriented solutions. Solid understanding of transaction and information systems, data warehouses, data marts, ODS, MDM methodologies and life cycle as well as ETL and MDM technologies.
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