Work Location:New York, New York, United States of America
Hours:40
Pay Details:$200,000 - $280,000 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:The Head of 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, FinOps, 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 AccountabilitiesEnterprise 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 technology management and governance.
- Define KPI frameworks, measurement standards, and reporting methodologies.
- Deliver trusted dashboards, scorecards, and executive reporting through Power BI and enterprise reporting platforms.
- Support stakeholders in measuring operational performance, technology health, risk exposure, and strategic outcomes.
User Experience, Report Design & Adoption- Ensure dashboards and data products are intuitive, actionable, and aligned to stakeholder needs.
- Drive persona-based reporting strategies for executives, risk teams, infrastructure teams, cyber teams, engineers, and technology leaders.
- Establish enterprise visualization and reporting standards.
- Measure dashboard adoption, effectiveness, and business value realization.
Stakeholder Management & Leadership- Build strong partnerships across Infrastructure, Cybersecurity, Enterprise Architecture, Finance, Risk, Data, Audit, and Engineering teams.
- Influence senior executives and stakeholders on enterprise data priorities and standards.
- Lead cross-functional initiatives that require coordination across business and technology domains.
- Champion a culture of data-driven decision-making and accountability.
Education & ExperienceEducation- Bachelor's Degree in Computer Science, Engineering, Information Technology, Data Management, Information Systems, or a related discipline.
- Master's Degree preferred (MBA, Data Science, Information Management, or Enterprise Architecture).
- Industry certifications such as Databricks, TOGAF, DAMA CDMP, ITIL, Cloud Provider Certifications (Azure, AWS, GCP) are preferred.
Experience- 12+ years of progressive experience in enterprise data management, data architecture, analytics, data governance, or technology strategy.
- 7+ years in a senior leadership role managing large-scale data, technology, or transformation programs.
- Proven experience building enterprise data lakes, data fabrics, or data platforms using Databricks or equivalent technology.
- Deep expertise in data governance, metadata management, taxonomy development, and common data model design.
- Experience delivering enterprise reporting and analytics solutions using Power BI or similar platforms.
- Experience integrating complex technology data from multiple systems of record using APIs, event-driven architectures, and modern data integration patterns.
- Strong understanding of infrastructure, cybersecurity, cloud, AI, and enterprise technology environments.
- Experience operating in highly regulated industries and supporting audit, regulatory, and risk management requirements.
- Demonstrated success influencing senior executives and leading cross-functional transformation initiatives.
Physical Requirements:Never: 0%; Occasional: 1-33%; Frequent: 34-66%; Continuous: 67-100%
- Domestic Travel - Occasional
- International Travel - Occasional
- 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 sense to deal with problems involving standardized situations - Continuous
- Reading, writing and comprehending instructions - Continuous
- Adding, subtracting, multiplying and dividing - Continuous
The above statements are intended to describe the general nature and level of work being performed by people assigned to this job. They are not intended to be an exhaustive list of all responsibilities, duties and skills required. The listed or specified responsibilities & duties are considered essential functions for ADA purposes.
