Data Quality Specialist

About the role

We are seeking an experienced Data Quality Specialist to lead enterprise‑wide data quality management for a major banking institution. The role will shape data quality strategy, implement controls, and ensure compliance with governance and regulatory standards.

Key responsibilities

• Define and implement enterprise data quality strategies, policies, standards, and frameworks aligned with the bank’s Data Governance strategy.
• Identify Critical Data Elements (CDEs) and establish data quality rules, thresholds, controls, and KPIs.
• Drive data quality improvement initiatives across Retail, Corporate, International, Treasury, Risk, Finance, Compliance and other support functions.
• Design measurement frameworks covering accuracy, completeness, consistency, validity, timeliness and uniqueness.
• Develop and maintain dashboards, reports, scorecards and KPIs to monitor data quality trends.
• Investigate, remediate and root‑cause data quality issues, delivering corrective action plans.
• Collaborate with technology and data engineering teams to automate data quality controls and validation rules.
• Act as a Data Quality SME, advising business, risk, finance, compliance, data owners and stewards.
• Embed data quality requirements into business processes, data models, pipelines and reporting solutions.
• Evaluate and implement modern data quality, governance, catalog and analytics technologies, leveraging AI/ML for profiling and anomaly detection.
• Lead platform modernization and migration from legacy solutions to contemporary tools.

Required profile

• 14+ years of experience in banking, data management, data governance or related fields.
• Minimum 10 years of hands‑on data quality and governance experience, preferably in financial services.
• Strong understanding of banking processes, systems, data domains and regulatory requirements.
• Proven ability to design and execute data quality strategies and remediation programs.
• Experience leading cross‑functional initiatives and working with senior stakeholders.

Required skills

• Advanced SQL for data analysis and profiling.
• AI/ML techniques for data profiling, anomaly detection and automation.
• Familiarity with modern data quality and data governance platforms.
• Strong knowledge of data quality dimensions (accuracy, completeness, consistency, etc.).