Data Quality Lead

About the Role

Linnk Group invites an experienced Data Quality Lead to spearhead the creation and management of a comprehensive enterprise-wide Data Quality Management Framework. This role is crucial to guarantee that data used in various domains—business operations, regulatory compliance, risk management, finance, analytics, and AI functions—is precise, complete, consistent, timely, and suitable for intended purposes.

Key Responsibilities

• Develop and uphold the Data Quality Framework including standards, procedures, control mechanisms, KPIs, KRIs, and performance scorecards.
• Define data quality parameters focusing on accuracy, completeness, consistency, validity, timeliness, uniqueness, and integrity and monitor them continuously.
• Set quality benchmarks for Critical Data Elements (CDEs) and generate dashboards and management reports based on these standards.
• Lead the management of data quality issues through evaluation of impacts, root cause analysis, remediation tracking, validations, and raising escalations when necessary.
• Supervise data quality aspects relevant to regulatory demands, financial and risk reporting, compliance, and management reviews, including preparation for audits.
• Ensure that data supporting AI, machine learning, and other advanced analytical applications adhere to quality standards.
• Collaborate closely with Data Owners, Data Stewards, and cross-functional teams in IT, Risk, Compliance, Finance, Operations, and Business units to maintain data integrity.
• Align all data quality activities with existing Data Governance and Data Management policies.

Qualifications and Experience

• Bachelor's degree in Computer Science, Data Analytics, Information Management, Business Administration, or related disciplines.
• Between 8 to 12 years of professional experience in areas such as Data Governance, Data Quality, Data Management, Risk Data Management, or Regulatory Reporting.
• Essential experience in sectors like Banking, Financial Services, or other strictly regulated industries.
• In-depth understanding of Data Quality Management, Data Governance, Data Lineage, Metadata and Reference Data Management, and Master Data Management (MDM).
• Hands-on exposure to platforms such as Informatica, Collibra, Microsoft Purview, ABACUS, or comparable Data Governance/Data Quality software.
• Proven capabilities in stakeholder engagement, analytical thinking, problem-solving, and effective communication.
• Preferred experience in regulatory reporting, risk data handling, audit processes, and AI/ML data quality maintenance.