Work Location:Toronto, Ontario, Canada
Hours:37.5
Line of Business:Technology Solutions
Pay Details:$115,600 - $163,200 CAD
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Job Description:The Senior Manager, Enterprise Data Quality Management owns and leads Data Content Manager as an enterprise capability across the ServiceNow modules that depend on trusted data. The role is accountable for establishing and operating the governance, controls, processes, and team required to continuously measure and improve data quality, completeness, accuracy, timeliness, consistency, and relationship integrity.
This leader owns the Data Content Manager blueprint framework, deviation-management process, certification cycles, data quality reporting, and control-testing program across the Configuration Management Database, Technology Reference Model, Application Portfolio Management, Hardware Asset Management, Software Asset Management, and other ServiceNow modules brought into scope.
The role partners with ServiceNow platform teams, data and asset owners, technology leaders, risk partners, and control functions to translate business, regulatory, and operational requirements into automated data quality rules and sustainable remediation processes. The Senior Manager ensures that ServiceNow systems of record remain reliable, decision-ready, and audit-ready.
KEY ACCOUNTABILITIESEnterprise Capability Ownership- Own the enterprise strategy, operating model, roadmap, and ongoing operation of Data Content Manager across all in-scope ServiceNow modules.
- Establish Data Content Manager as the enterprise capability for continuously monitoring, identifying, routing, remediating, and certifying data quality issues.
- Define the phased expansion of Data Content Manager across the Configuration Management Database, Technology Reference Model, Application Portfolio Management, Hardware Asset Management, Software Asset Management, and other ServiceNow data domains.
- Serve as the senior business owner for the capability, setting priorities and managing the product backlog in partnership with ServiceNow platform and engineering teams.
- Ensure the capability is scalable, sustainable, and aligned with Enterprise Technology Asset Management standards, enterprise data governance requirements, and ServiceNow platform strategy.
Data Quality Governance and Blueprint Management- Own the enterprise data quality rulebook and the complete inventory of Data Content Manager blueprints.
- Define standards for blueprint design, approval, testing, deployment, monitoring, amendment, exception, and retirement.
- Translate business rules, control requirements, data definitions, and regulatory expectations into automated validations that test the correct records, fields, relationships, and conditions.
- Establish measurable quality thresholds for completeness, accuracy, validity, consistency, timeliness, uniqueness, ownership, lifecycle status, and relationship integrity.
- Govern changes to blueprint conditions, assignment logic, remediation timelines, and certification requirements through documented change control.
- Ensure each blueprint has a defined business purpose, accountable owner, authoritative source, remediation path, and evidence trail.
- Identify and address duplicate, conflicting, obsolete, or ineffective rules across ServiceNow modules.
Continuous Monitoring, Deviation Management, and Certification
- Operate the end-to-end deviation-management lifecycle, including scheduled scans, task generation, assignment, notification, validation, closure, escalation, and reporting.
- Establish service levels and escalation paths for overdue, recurring, rejected, or un-routable deviations.
- Lead periodic field-level certification campaigns across in-scope ServiceNow modules, ensuring that certification responsibilities align with data ownership and segregation-of-duties requirements.
- Define and operate group certification processes for fields owned by specialist or centralized functions.
- Ensure proposed data corrections are appropriately validated and implemented through approved workflows.
- Monitor remediation volumes, aging, recurrence, rejection rates, routing failures, and closure quality to identify systemic issues.
- Maintain an auditable record of blueprint execution, deviations, approvals, certifications, exceptions, and remediation activity.
Data Quality Assurance and Control Testing- Establish and execute a first-line data quality assurance and control-testing program across the Enterprise Technology Asset Management control environment.
- Design test procedures, select appropriate populations or samples, document results, identify control deficiencies, and report conclusions that can withstand independent challenge.
- Validate that Data Content Manager rules detect the intended data conditions and that remediation and certification processes operate as designed.
- Perform root-cause analysis of recurring or material data defects and determine whether corrective action is required in data, process, ownership, integration, discovery, or platform configuration.
- Track control gaps, management actions, and remediation commitments through closure.
- Support regulatory examinations, internal audit reviews, risk assessments, and issue-remediation programs with clear, complete, and traceable evidence.
- Partner with risk, compliance, audit, and governance functions to demonstrate the effectiveness and sustainability of data quality controls.
Metrics, Reporting, and Executive Oversight- Own the enterprise data quality measurement framework and reporting cadence across all modules in scope.
- Define and monitor key performance and risk indicators, including compliance scores, data completeness and accuracy, on-time remediation, aged deviations, recurring defects, unrouteable tasks, certification completion, and control-test results.
- Produce dashboards, scorecards, and executive reporting that translate technical data quality results into operational, regulatory, and business risk.
- Identify material trends, concentrations, and emerging risks and recommend prioritized corrective actions.
- Provide transparent reporting to senior leadership and governance forums, including clear ownership, target dates, dependencies, and escalation requirements.
- Measure the effectiveness of blueprints and remediation activity, not only the volume of tasks created or closed.
Stakeholder Governance and Accountability- Partner with ServiceNow platform teams, module owners, Asset Class and Sub-Class Owners, data owners, technology and business asset owners, architecture, infrastructure, security, risk, and audit.
- Establish clear decision rights and accountability across data consumers, data owners, and data providers.
- Facilitate prioritization of cross-domain data quality issues and resolve conflicts involving rule ownership, remediation responsibility, and authoritative data sources.
- Influence senior stakeholders to address data quality issues where accountability is distributed and direct authority is limited.
- Promote data quality as a shared enterprise responsibility supported by clear governance, practical workflows, training, and transparent reporting.
- Represent the Data Content Manager capability in governance forums, platform planning, control reviews, and regulatory or audit discussions.
Team Leadership and Operational Management- Build, lead, and develop a team responsible for blueprint engineering, data quality operations, certification, reporting, control testing, and stakeholder support.
- Establish clear roles, responsibilities, performance objectives, operating procedures, and service expectations for the team.
- Plan team capacity and skills as additional ServiceNow modules and data domains are brought into scope.
- Foster a culture of disciplined execution, evidence-based decision-making, constructive challenge, and continuous improvement.
- Ensure operational documentation, runbooks, training materials, support processes, and knowledge articles remain current.
- Manage vendor or consulting resources where specialized implementation or technical expertise is required.
ScopeServiceNow Modules- Configuration Management Database
- Technology Reference Model
- Application Portfolio Management
- Hardware Asset Management
- Software Asset Management
- Additional ServiceNow modules and data domains approved for inclusion
Key Artifacts Owned- Data Content Manager operating model and roadmap
- Enterprise data quality rulebook
- Blueprint inventory, design standards, and change records
- Deviation-management and escalation procedures
- Certification plans, task records, and completion evidence
- Data quality key performance indicators, scorecards, and dashboards
- Control-testing plans, evidence, results, and remediation tracking
- Data quality governance procedures, runbooks, and training materials
EXPERIENCE & EDUCATION- Ten or more years of progressive experience in data quality management, data governance, technology asset management, configuration management, technology risk, or a related discipline.
- Five or more years of experience leading teams or enterprise-scale programs in a large, complex organization.
- Demonstrated ownership of a data quality, governance, configuration management, or ServiceNow platform capability.
- Strong working knowledge of ServiceNow, including the Configuration Management Database, Application Portfolio Management, Hardware Asset Management, Software Asset Management, Technology Reference Model, or related modules.
- Experience designing automated data quality rules, validation controls, remediation workflows, certification processes, and executive reporting.
- Strong understanding of data quality dimensions, including completeness, accuracy, validity, consistency, timeliness, uniqueness, ownership, and relationship integrity.
- Experience establishing data ownership, stewardship, accountability, service levels, and escalation mechanisms across federated organizations.
- Demonstrated control-testing capability, including test design, population or sample selection, evidence collection, issue identification, and defensible reporting.
- Experience supporting internal audit, regulatory, compliance, or risk-management requirements in a regulated environment.
- Strong analytical and problem-solving skills, with the ability to identify root causes and distinguish data defects from process, integration, discovery, ownership, or platform issues.
- Strong executive communication skills and the ability to translate technical data quality results into business and operational risk.
- Proven ability to influence senior stakeholders and drive remediation where responsibility is distributed across multiple teams.
- Experience leading change, developing teams, and establishing new enterprise capabilities or operating models.
Preferred Qualifications- Financial services experience.
- ServiceNow certifications relevant to platform administration, the Configuration Management Database, Application Portfolio Management, Hardware Asset Management, or Software Asset Management.
- Familiarity with the Common Service Data Model and ServiceNow relationship and dependency structures.
- Experience with data profiling, querying, health dashboards, automated testing, or analytics tools.
- Familiarity with technology asset lifecycle management, operational resilience, and regulatory expectations for trusted systems of record.
- ITIL, COBIT, data governance, risk, audit, or related professional certification.
