Data Quality Lead

Kelly; Toronto; Hybrid; CAD 130,000 - 150,000; Full time

Job summary

Kelly is seeking a Data Quality Management Lead to drive enterprise-wide data quality strategy, governance, controls, and continuous improvement in a hybrid Toronto/Burlington environment. Partner with data owners and stewards to ensure data is accurate, complete, and fit for purpose.

You will design rules, dashboards, and KPIs, embed controls across ETL/ELT, MDM, and cloud platforms, and leverage AI tools to automate remediation. Strong SQL and DQ platform experience are required.

Qualifications

• Experience with Data Quality, Data Governance, or Enterprise Data Management.
• Strong SQL, data profiling, reconciliation, and DQ rule development experience.
• Experience with Informatica, Collibra, Talend, Ataccama, or similar DQ platforms.
• Strong understanding of metadata, lineage, CDEs, data governance, and controls.
• Experience with AI tools such as GitHub Copilot, Claude Code, OpenAI Codex, Cursor, or VS Code.

Responsibilities

• Lead enterprise Data Quality frameworks, standards, controls, and processes.
• Design DQ rules, profiling, validation, reconciliation, monitoring, and issue management.
• Establish DQ ownership, SLAs, root-cause analysis, and remediation processes.
• Build DQ dashboards, KPIs, scorecards, and executive reporting.
• Embed DQ controls across ETL/ELT, MDM, cloud, data lake, and modern data platforms.
• Leverage AI, LLMs, Agentic AI, and AI-assisted development tools to automate DQ monitoring and remediation.

Skills

Data Quality

SQL

Data governance

ETL/ELT

AI tools

Cloud data platforms

Education

Bachelor's degree

Tools

Informatica

Collibra

Talend

Ataccama

Databricks

Job description

Salary Range: $130K - $150 K Base + Benefits

Location: Toronto, ON or Burlington, ON (Hybrid)

About the Role

We are looking for a Data Quality Management Lead to drive enterprise-wide Data Quality strategy, governance, controls, and continuous improvement. The role will partner with Data Governance, Architecture, Engineering, Data Owners, and Stewards to ensure critical data is accurate, complete, consistent, and fit for purpose.

Key Responsibilities:

• Lead enterprise Data Quality frameworks, standards, controls, and processes.
• Design DQ rules, profiling, validation, reconciliation, monitoring, and issue management.
• Establish DQ ownership, SLAs, root-cause analysis, and remediation processes.
• Build DQ dashboards, KPIs, scorecards, and executive reporting.
• Embed DQ controls across ETL/ELT, MDM, cloud, data lake, and modern data platforms.
• Leverage AI, LLMs, Agentic AI, and AI-assisted development tools to automate DQ monitoring and remediation.

Requirements:

• - Experience with Data Quality, Data Governance, or Enterprise Data Management.
• - Strong SQL, data profiling, reconciliation, and DQ rule development experience.
• - Experience with Informatica, Collibra, Talend, Ataccama, or similar DQ platforms.
• - Strong understanding of metadata, lineage, CDEs, data governance, and controls.
• - Experience with AI tools such as GitHub Copilot, Claude Code, OpenAI Codex, Cursor, or VS Code.
• - Azure/Databricks experience is a plus.
• - Knowledge of BCBS 239, GDPR, SOX, or ISO 8000 is preferred.