AVP, Infrastructure & Engineering, Technology Data Management

## AVP, Infrastructure & Engineering, Technology Data Management Apply remote type:
On Site locations:
Toronto, Ontario time type:
Full time posted on:
Posted Todaytime left to apply:
End Date:
July 31, 2026 (12 days left to apply) job requisition :
R 1500002
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* Work Location:

** Toronto, Ontario, Canada
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* Hours:

** 37.5
** Line of Business:
** Technology Solutions
** Pay Details:**$175,000 - $215,000 CADTD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience  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.
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* Job Description:

** The AVP, Technology Data Management is responsible for establishing and leading the enterprise capability for managing, governing, and operationalizing technology reference data across infrastructure, cyber, cloud, AI, and enterprise technology domains. The role will build and operate a Databricks-based data fabric that transforms fragmented technology data from multiple systems of record into a trusted, authoritative, and consumable enterprise asset.

This leader will define and implement data governance, taxonomies, common data models, metadata standards, and data products that enable enterprise-wide reporting, analytics, risk management, Fin Ops, operational management, and executive decision-making. The role serves as the central authority for technology reference data, ensuring data is accurate, governed, discoverable, and accessible through modern consumption channels including APIs, Power BI, and enterprise reporting platforms.
** Key Accountabilities
**** Enterprise Technology Data Strategy
*** Define and lead the enterprise strategy, operating model, and roadmap for technology reference data.
* Establish a scalable technology data fabric leveraging Databricks as the enterprise platform for technology data integration and consumption.
* Create a long-term vision for trusted technology data that supports enterprise governance, reporting, analytics, operational management, and risk oversight.
* Drive enterprise adoption of common data standards, governance practices, and technology data products.
** Data Governance & Quality Management
*** Establish governance frameworks to ensure technology data is accurate, complete, authoritative, compliant, and fit for purpose.
* Define data ownership, stewardship, accountability, and quality controls across technology domains.
* Implement controls, monitoring, and remediation processes to improve ongoing data quality.
* Ensure data management practices align with regulatory, audit, risk, security, and compliance requirements.
** Metadata, Data Dictionary & Data Marketplace
*** Own the enterprise technology data dictionary and business glossary.
* Establish and maintain metadata standards, data lineage, and data cataloguing capabilities.
* Create a technology data marketplace that enables stakeholders to discover, understand, and consume enterprise data assets.
* Drive consistent interpretation of technology data across the organization.
** Common Taxonomy & Data Modeling
*** Define and maintain a common technology taxonomy spanning infrastructure, cyber, cloud, AI, applications, services, products, assets, risks, and capabilities.
* Establish canonical data models and enterprise data relationships across technology domains.
* Ensure technology data is standardized across systems and reporting platforms.
* Drive consistency in definitions, classifications, hierarchies, and business rules.
** Data Products & Information Services
*** Define and govern enterprise technology data products aligned to business and operational use cases.
* Translate complex technical data into business-consumable products that support decision-making.
* Establish standards for reusable data assets, semantic layers, APIs, and reporting services.
* Prioritize data products based on business value, risk reduction, and strategic objectives.
** Data Engineering & Platform Enablement
*** Lead onboarding of technology systems of record into Databricks through APIs, event-based integrations, streaming capabilities, and zero-copy architectures.
* Establish enterprise standards for data integration, ingestion, transformation, and observability.
* Ensure scalable, resilient, and secure data pipelines that support enterprise consumption.
* Partner with engineering teams to optimize platform performance and data delivery capabilities.
** Reporting, Analytics & Metrics
*** Establish enterprise reporting and analytics capabilities for…