Data Governance Lead

K&K Global Talent Solutions INC.; Toronto; On-site; CAD 140,000 - 210,000; Full time

Job summary

K&K Global Talent Solutions INC. seeks a Senior Data Governance Lead to architect and steer enterprise data governance, quality, lineage and observability across complex data platforms.

You will shape governance policies, standards and operating models and drive adoption with risk, compliance, data engineering and business units. You will partner across Azure, AWS, Databricks and Snowflake to ensure compliant data management, lineage, and data quality.

Qualifications

• 12+ years of enterprise data management with governance, quality, lineage and observability.

Responsibilities

• Lead discovery workshops, current/target-state design and roadmaps.
• Define enterprise governance operating models, policies, controls and decision rights.
• Establish data quality frameworks with profiling, rules, scorecards and issue management.
• Implement data observability for freshness, volume, schema and incidents.
• Embed governance across cloud, lakehouse, DW, data integration and analytics ecosystems.
• Mentor data governance leads, stewards and engineers; deliver reusable accelerators.

Skills

Leadership

Stakeholder mgmt

Data governance

Communication

Education

DAMA/CDMP certification

DCAM certification

Tools

Collibra

Informatica CDGC/Axon/EDC/IDQ

Microsoft Purview

Alation

Atlan

BigID

Monte Carlo

Bigeye

Unity Catalog

Job description

12-16 years overall, including 7+ years in Data Governance/Data Management and 3+ years in a lead or architecture role

Must Have Technical/Functional Skills:

• 12+ years of experience in enterprise data management, with strong expertise across Data Governance, Data Quality, Metadata, Data Lineage and Data Observability.
• Proven experience defining and implementing enterprise Data Governance operating models, policies, standards, controls, stewardship structures, decision rights and governance forums.
• Strong hands-on knowledge of business and technical metadata, data catalog, glossary, classification, ownership, critical data elements and end-to-end lineage.
• Deep understanding of Data Quality frameworks, including profiling, rule design, controls, scorecards, issue management, root-cause analysis, remediation and continuous monitoring.
• Experience establishing Data Observability capabilities spanning freshness, volume, schema, distribution, pipeline health, anomalies, incidents, service levels and operational dashboards.
• Ability to integrate governance, quality, lineage and observability controls across cloud, lakehouse, data warehouse, data integration and analytics ecosystems.
• Experience with one or more enterprise platforms such as Collibra, Informatica CDGC/Axon/EDC/IDQ, Microsoft Purview, Alation, Atlan, BigID, Monte Carlo, Bigeye, Databricks Unity Catalog or comparable tools.
• Strong knowledge of data architecture, data modeling, ETL/ELT, APIs, batch/streaming pipelines, SQL and cloud data platforms such as Azure, AWS, Databricks or Snowflake.
• Experience defining governance and quality KPIs/KRIs, control evidence, data issue workflows, auditability and executive reporting.
• Good understanding of privacy, security, retention, regulatory and risk-management expectations relevant to financial services, including BCBS 239, GDPR/CCPA and data-control principles.
• Proven experience leading discovery workshops, current-state assessments, target-state design, roadmaps, tool evaluations, implementation planning and adoption/change initiatives.
• Strong consulting, stakeholder-management and communication skills, with the ability to engage business, risk, compliance, data, engineering and executive stakeholders.
• Preferred certifications in DAMA/CDMP, DCAM, Collibra, Informatica, Microsoft Purview, cloud data platforms, data quality or related disciplines.
• Lead the design and implementation of an integrated Data Governance, Data Quality, Data Lineage and Data Observability capability for enterprise data platforms.
• Translate business, regulatory, risk and technology needs into pragmatic governance policies, standards, controls, processes and implementation roadmaps.
• Define the operating model, including accountable data owners, business and technical stewards, governance councils, RACI, escalation paths and decision rights.
• Establish enterprise metadata, business glossary, data catalog, classification, critical data element and ownership practices.
• Design Data Quality lifecycle processes covering profiling, rule definition, thresholds, monitoring, scorecards, issue triage, root-cause analysis and remediation governance.
• Define and operationalize end-to-end lineage from source through transformations to reports, analytics, regulatory outputs and AI use cases.
• Establish observability monitoring for data freshness, completeness, volume, schema, distribution, pipeline reliability, anomalies and data incidents; align alerts with support and remediation workflows.
• Develop control frameworks, KPIs/KRIs, dashboards and executive reporting to demonstrate data health, control effectiveness, risk reduction and adoption.
• Evaluate and configure governance tooling; define integration patterns with data platforms, ETL/ELT, BI, ticketing, CI/CD and cloud services.
• Partner with data architecture, engineering, platform, security, privacy, risk and business teams to embed governance controls within delivery lifecycle and DataOps practices.
• Lead workshops, architecture/design reviews, backlog prioritization, implementation governance, testing, release readiness and production adoption.
• Manage risks, dependencies and issues; provide clear recommendations and elevate decisions requiring senior stakeholder intervention.
• Mentor governance leads, data stewards, analysts and engineers; create reusable accelerators, templates, playbooks and knowledge assets.
• Support Solutioning, proposals, effort estimation, client presentations and capability development for Data Governance and Data Management opportunities.

Generic Managerial Skills, If any

• Strong leadership and stakeholder-management skills across business, technology, risk, compliance and data organizations.
• Excellent written, verbal and presentation skills for technical, business and executive audiences.
• Consultative problem-solving approach with the ability to simplify complex governance and technology topics.
• Experience leading cross-functional and geographically distributed teams and driving outcomes without direct authority.
• Strong planning, prioritization, facilitation, negotiation, risk management and decision-making skills.
• High ownership, accountability and attention to detail, with a focus on measurable adoption & sustainable operating practices.

Ability to mentor practitioners, influence senior stakeholders and establish an active data stewardship community