Data Architect, Technology Data Management

TD•Toronto, ON

10d•CA$155,000 - CA$215,000•Onsite

About The Position

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.

Requirements

Bachelor's Degree in Computer Science, Information Systems, Data Management, Engineering, Mathematics, or a related discipline.
8-12+ years of experience in data architecture, enterprise architecture, information management, or data modeling.
Proven experience defining enterprise taxonomies, metadata frameworks, and common data models.
Strong experience in designing data architectures for cloud-based data platforms, preferably Databricks.
Experience integrating multiple systems of record into common enterprise data structures.
Demonstrated expertise in data governance, metadata management, lineage, and data quality frameworks.
Experience supporting enterprise reporting, analytics, and business intelligence initiatives.
Strong understanding of infrastructure, cybersecurity, cloud, AI, and technology management domains.
Experience working in large, complex, and highly regulated organizations.
Excellent stakeholder management, facilitation, and communication skills.

Nice To Haves

Master's Degree preferred in Data Science, Information Management, Computer Science, or Enterprise Architecture.
Relevant industry certifications preferred: TOGAF, DAMA CDMP, Databricks Data Engineer or Architect Certification, Azure, AWS, or GCP Data Certifications, ITIL Foundation.

Responsibilities

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.
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.
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.
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.
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 providing architectural guidance and standards.
Ensure compliance with enterprise data policies and regulatory requirements.
Define the data structures and semantic models required to support enterprise data products.
Partner with Data Product Managers to translate business requirements into scalable information models.
Ensure data products use common definitions and standardized enterprise relationships.
Support creation of reusable, governed data assets that can be consumed through APIs, dashboards, and reports.
Collaborate with Enterprise Architecture, Infrastructure, Cybersecurity, Engineering, Finance, Risk, and Data teams.
Facilitate workshops to define business terms, classifications, and data relationships.
Act as a trusted advisor on technology data architecture, taxonomy, and modeling decisions.
Influence stakeholders toward adoption of common standards and enterprise models.