Senior Manager, Data Governance & Analytics
- Waterloo, ON
- Permanent
- Full-time
- Design, document, and operationalize a scalable Data Governance Framework aligned with organizational goals and regulatory requirements.
- Define roles and responsibilities for data governance participants, including Data Owners, Data Stewards, and Data Custodians.
- Creation of Data Governance Policies, Standards, and Processes
- Author and maintain data governance policies, data standards, and control procedures across data domains (e.g., customer, product, finance).
- Collaborate with legal, compliance, and business stakeholders to ensure alignment with internal policies and external regulations.
- Monitoring and Control
- Establish and execute governance control routines, including annual data certification, policy attestation, data domain health checks, and compliance monitoring.
- Ensure data-related controls are integrated into broader risk management processes.
- Education and Training
- Develop and deliver training programs and materials for data governance stakeholders, including onboarding for Data Stewards and recurring sessions for Data Owners.
- Promote data governance literacy across business units through workshops, webinars, and knowledge base development.
- Reporting and Stakeholder Engagement
- Provide regular updates and dashboards to the Data Governance Council and executive sponsors on data governance maturity, policy adherence, data quality, and remediation status.
- Act as the primary liaison between data governance and data-consuming functions.
- Create, maintain, and enhance metadata assets within MS Purview, including technical, business, and operational metadata.
- Define and enforce metadata standards, manage data catalogs, and ensure completeness of metadata attributes across systems.
- Document data lineage across key data flows to support traceability, regulatory reporting, and root cause analysis.
- Tagging and Data Classification
- Implement consistent tagging and data classification practices based on data sensitivity, usage, and regulatory impact.
- Collaborate with Information Security and Privacy teams to support data protection initiatives.
- Platform data and usage management
- Match the data tagging and lineage with a “per functional area” view so that we can understand the services that are provided to each of our business domains
- Define and implement a framework to understand the overall consumption of Fabric capacity and associate this with the costs
- Implement an impact assessment framework to understand what will happen when we add new functionality and data to the central data platforms – covering data volumes, compute capacity and the resultant extra resources needed
- Data Quality Management
- Define and operationalize data quality dimensions (e.g., completeness, accuracy, timeliness) and associated metrics.
- Design and maintain data quality rules and validations for priority data assets.
- Coordinate data profiling, anomaly detection, and remediation activities with Data Stewards and Data Owners.
- Develop periodic Data Quality Reports and dashboards, highlighting trends, anomalies, and remediation status.
- Data Cleansing and Remediation Oversight
- Oversee execution of data cleansing activities by business and IT teams, including root cause analysis and corrective/preventative actions (CAPAs).
- Coordinate with upstream/downstream system owners to prevent reoccurrence of data quality issues.