Data Architect, Technology Data Management

The pay details posted reflect a temporary market premium specific to this role that is reassessed annually. TD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience at TD. Our compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs. As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

The Data Architect,   Technology Data Management   role is responsible for designing, governing, and evolving the enterprise technology data architecture that underpins the organization's Technology Reference Data strategy. Reporting to the Head of Technology Reference Data, this position establishes the common taxonomy, canonical data models, metadata standards, and information architecture required to integrate technology data from infrastructure, cybersecurity, cloud, AI, and enterprise technology domains into a unified and authoritative data ecosystem.   The role serves as the architectural authority for technology reference data, ensuring data consistency, interoperability, scalability, and traceability across systems of record, data products, reporting platforms, and analytics solutions. This position plays a critical role in enabling enterprise governance, operational management, risk reporting, regulatory compliance, and executive decision-making through standardized and trusted data.   KEY ACCOUNTABILITIES: Enterprise Data Architecture   Define and maintain the enterprise technology reference data architecture.   Develop and govern canonical data models across infrastructure, cyber, cloud, AI, operational, and service management domains.   Establish architectural standards for technology data integration, storage, relationships, and consumption.   Define data architecture principles that support scalability, consistency, and enterprise-wide reuse.   Taxonomy & Metadata Management   Develop and maintain the enterprise technology taxonomy.   Standardize technology definitions, classifications, hierarchies, and naming conventions.   Establish metadata standards to support data quality, governance, traceability, and reporting consistency.   Partner with business and technology stakeholders to ensure shared understanding of technology data concepts.   Common Data Modeling   Design logical, conceptual, and physical data models that support enterprise technology data products.   Define relationships among applications, infrastructure assets, cloud services, technology products, capabilities, risks, controls, and business services.   Create reusable models that support enterprise reporting, analytics, and governance requirements.   Ensure data models support current and future technology platforms and business needs.   System of Record Strategy   Identify and document authoritative systems of record for technology domains.   Define rules for data sourcing, master data management, and authoritative ownership.   Establish traceability and lineage between source systems, data products, reports, and metrics.   Support onboarding and integration of new systems into the enterprise data fabric.   Data Governance & Quality   Partner with governance teams to define standards for data quality, completeness, and integrity.   Establish data validation rules and modeling standards that improve consistency across data domains.   Support stewardship activities by