About the Job

The Supervisor, Data Quality & Stewardship reports to the Assistant Manager –Data Quality & Stewardship. The jobholder is responsible for ensuring the accuracy, consistency, and trustworthiness of data used across the authority. This person enforces data quality standards, manages data assets, and supports governance initiatives to ensure data integrity for revenue collection, compliance, fraud detection, and reporting. The role also involves working closely with data owners, technology, and business units to drive a culture of data stewardship and accountability, and is responsible for the implementation and maintenance of Master Data Management (MDM) solutions.

Responsibilities

Develop and implement data quality frameworks, policies, and metrics tailored to tax administration systems and datasets.
Identify, monitor, and resolve data quality issues across core revenue-related domains (e.g., taxpayer records, filing data, payment history, customs processes, third-party data).
Maintain a business glossary, data catalog, metadata, and data lineage documentation for data assets in collaboration with data stewards and domain experts.
Facilitate the creation and enforcement of data stewardship processes, including ownership, lifecycle management, and change tracking.
Conduct root cause analysis of data quality issues and drive corrective actions.
Support regulatory reporting and audit compliance by ensuring high-quality, traceable data.
Collaborate with data engineers and business analysts to ensure data pipelines and reports reflect current quality, data standards, ownership models, and governance policies for master data.
Perform data profiling, cleansing, deduplication, and matching to improve the quality and consistency of master data records.
Contribute to the development and implementation of data governance tools and platforms.
Coordinate the execution of data profiling, data validation, and data cleansing activities across different departments.
Work closely with business units, data owners, and technical teams to understand data requirements and address quality issues related to specific data domains.
Lead data quality audits to ensure data governance policies and standards are being adhered to across systems and processes.
Produce regular reports and dashboards on data quality status, trends, and improvement efforts for leadership and key stakeholders.
Define and track key performance indicators (KPIs) related to data quality and MDM, ensuring measurable progress toward organizational data quality objectives.
Maintain and update master data records in accordance with established standards and ensure data quality and master data management (MDM) processes are aligned with the organization’s data governance framework and comply with relevant data protection regulations.
Implement tools and technologies for MDM, data quality management, data profiling, and data cleansing to improve efficiency and effectiveness.
Provide support and training to data stewards and business users on data quality and MDM processes and tools.
Participate in data governance committees and working groups to support cross-functional data initiatives and the organization’s overall data strategy.

Requirements

A Bachelor’s Degree in Information Technology/Business Information Technology, Computer Science, Mathematics, Data Science, Economics, Communications, Information Science or related field from a recognized institution.
Professional qualification in Data Quality, Data Management, Data Governance, Data Analytics or a related field.
Minimum of 3 years work experience in a similar role.
Familiarity with data privacy regulations and standards.
Technical proficiency in: application of tools for data profiling, cleansing, and validation; design and implement data quality rules and frameworks; Data management /governance frameworks such as DAMA-DMBOK; knowledge of regulatory & compliance requirements; familiarity with metadata management and master data management; experience using data cataloguing tools.
Supervisory skills.
Strong analytical and problem-solving skills.
Excellent communication skills for engaging both technical and non-technical stakeholders.
Proactive and results-oriented mindset.
Exceptional attention to detail and commitment to data accuracy.
Adaptability and openness to learning new technologies.
Ability to collaborate with cross-functional teams effectively.
Integrity and discretion when handling sensitive or confidential data.