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TD Bank

Offers banking, loans, and wealth management.

Data Architect - Technology Data Management

Data ManagementConfirmed live in the last 24 hours
Full-timeToronto, ON, CanadaCA$155k - CA$215kIn-person

About the Job

Requirements

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

Responsibilities

  • Define and maintain the enterprise technology reference data architecture.
  • Develop and govern canonical data models across infrastructure, cyber, cloud, artificial intelligence, 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 application programming interfaces, 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.

Desired Qualifications

  • A Master's degree in Data Science, Information Management, Computer Science, or Enterprise Architecture is preferred.
  • TOGAF certification is preferred.
  • DAMA CDMP certification is preferred.
  • Databricks Data Engineer or Architect certification is preferred.
  • Azure, AWS, or GCP data certifications are preferred.
  • ITIL Foundation certification is preferred.

About the Company

TD Bank

Offers banking, loans, and wealth management.

TD Bank provides a wide range of banking and financial services in North America for individuals, businesses, and corporations. Core offerings include checking and savings accounts, credit cards, loans, mortgages, investment products, and wealth management. TD Bank emphasizes digital banking through online and mobile apps that let customers manage money, pay bills, deposit checks, transfer funds, and manage cards. Revenue comes from interest on loans, service fees, and investment income. The company differentiates itself with a broad product lineup, large North American footprint, and integrated services for both personal and business customers, plus a focus on digital accessibility. Its goal is to be a leading, accessible financial institution that helps customers manage and grow their money through convenient, everyday banking and investment solutions.

Company size
10,001+
Company stage
IPO
Headquarters
Toronto, Canada
Founded
1955

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