Data Architecture, Taxonomy & Modeling Principal Architect (US)

Work Location:

Mount Laurel, New Jersey, United States of America

Hours:

40

Pay Details:

$148,720 - $223,080 USD

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.

Line of Business:

Technology Solutions Job Description:

Data Architect, Technology Data Management

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 Responsibilities

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 providing architectural guidance and standards.

Ensure compliance with enterprise data policies and regulatory requirements.

Data Products Enablement

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.

Stakeholder Engagement

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.

Depth & Scope:

• •Top technical individual contributor role with accountability to guide technology selection through expert knowledge of the catalogue of technology stacks and practices associated with platforms, programming, languages and tools, as well as advanced business acumen and understanding of broader organization issues and relevant technology
• •Accountable for the overall Architecture portfolio, roadmap and definition in the product-based org for their respective journey or platform
• •Responsible for strategic decisions for the Architecture practice within a platform or journey, escalating as appropriate
• •Sets collaboration framework and create solution prototypes for providing Architecture advice and guidance to the product-based org
• •Controls solution and development, regulatory and compliance for complex system landscapes (e.g., hybrid, multi-cloud, edge workloads)

Education & Experience:

• •Undergraduate degree or Technical Certificate (Graduate degree preferred)
• •15+ years relevant experience developing a variety of platforms
• •Experience with Continuous Integration, Continuous Delivery, Pair programming and / or Test-Driven Development is an asset (i.e., ability to author Unit, Integration and Functional Tests)
• •Demonstrated experience with leading technical tools integration in a complex environment

Preferred Qualifications:

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.

Physical Requirements:

Never: 0%; Occasional: 1-33%; Frequent: 34-66%; Continuous: 67-100%

• •Domestic Travel – Occasional
• •International Travel – Never
• •Performing sedentary work – Continuous
• •Performing multiple tasks – Continuous
• •Operating standard office equipment - Continuous
• •Responding quickly to sounds – Occasional
• •Sitting – Continuous
• •Standing – Occasional
• •Walking – Occasional
• •Moving safely in confined spaces – Occasional
• •Lifting/Carrying (under 25 lbs.) – Occasional
• •Lifting/Carrying (over 25 lbs.) – Never
• •Squatting – Occasional
• •Bending – Occasional
• •Kneeling – Never
• •Crawling – Never
• •Climbing – Never
• •Reaching overhead – Never
• •Reaching forward – Occasional
• •Pushing – Never
• •Pulling – Never
• •Twisting – Never
• •Concentrating for long periods of time – Continuous
• •Applying common s