Data Quality Lead

Role Summary

Nair Systems is looking for an experienced Data Quality Lead to join its operations in Qatar. The position is pivotal in steering enterprise-wide data quality governance, continuous monitoring, issue resolution, regulatory compliance reporting, and enabling data quality for AI and analytics applications.

Qualifications and Experience

• A Bachelor's degree in Information Management, Computer Science, Data Analytics, Business Administration, or a similar discipline is required.
• Possess between 8 to 12 years of expertise in data governance, data quality assurance, data management, risk data oversight, regulatory reporting, or closely related fields.
• Prior work experience in banking, financial services, or other heavily regulated sectors is mandatory.
• Strong familiarity with data quality management practices, including data governance, data lineage tracking, metadata handling, reference data, and master data management.
• Experience using enterprise data platforms such as Informatica, Collibra, Microsoft Purview, ABACUS, or equivalent data solutions.

Key Responsibilities

• Establish, refine, and sustain the data quality framework, encompassing standards, procedures, methodologies, and operational models.
• Set out data quality principles, implement controls, and establish KPIs, KRIs, scorecards, and comprehensive reporting criteria.
• Ensure alignment of practices with broader data governance policies and regulatory mandates, including compliance with Qatar Central Bank (QCB) requirements.
• Define and manage monitoring rules ensuring data accuracy, completeness, consistency, validity, timeliness, uniqueness, and integrity across critical data elements in business and support domains.
• Provide enterprise-wide data quality performance reporting through dashboards, scorecards, and management updates.
• Deliver insights on data quality trends, risks, and remediation efforts to governance bodies and senior leadership.
• Lead the identification of data quality issues including impact assessments, root cause analysis, remediation tracking, and validation of fixes.
• Maintain a centralized data quality issue registry and rigorously challenge remediation plans from data custodians and technology teams.
• Escalate significant risks and unresolved issues to governance committees for prompt action.
• Oversee control frameworks supporting regulatory, financial, risk, compliance, and management reporting requirements.
• Collaborate with Risk, Finance, Compliance, and business units to ensure adherence to regulatory data quality standards.
• Support regulatory audits, examinations, and data quality reviews.
• Evaluate and manage data quality risks that impact AI models, facilitating controls throughout the data and AI lifecycle.
• Engage with a broad spectrum of stakeholders including data owners, stewards, business units, IT, and subsidiaries to promote data quality stewardship and accountability.
• Lead working groups and governance forums focused on continuous improvement of data quality.