12-16 years overall, including 7+ years in Data Governance/Data Management and 3+ years in a lead or architecture roleMust 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. ~ Robust 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; 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. 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. Strong planning, prioritization, facilitation, negotiation, risk management and decision-making skills. Ability to mentor practitioners, influence senior stakeholders and establish an active data stewardship community #

📌 Data Governance Lead (Winnipeg)
🏢 Ku0026K Global Talent Solutions
📍 Winnipeg