Data Quality Specialist (Arabic Speaker)
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About the Role
Data Quality Specialist – Roles & Responsibilities * The Data Quality Specialist is responsible for designing, implementing, and managing data quality controls across the Program.
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Data Quality Specialist – Roles & Responsibilities
- The Data Quality Specialist is responsible for designing, implementing, and managing data quality controls across the Program. The role operates at the intersection of Data Governance, Master Data Management (MDM), and Registry Operations, ensuring that trusted data related to individuals, businesses, and assets meets established quality standards before and after publication through Registry-as-a-Service (RaaS) APIs.
- Develop and implement data quality rules for records pertaining to individuals, establishments, and assets in alignment with the DAMA-DMBOK2 framework and ISO 8000 standards, including the definition of quality thresholds, risk classifications, and automated remediation mechanisms.
- Conduct comprehensive data profiling and exploratory analysis of source systems feeding the registry, documenting baseline data quality metrics and assessing readiness prior to migration activities based on findings from the program’s initial phase.
- Translate business requirements from Data Owners and Data Stewards into actionable data quality rules that address all key quality dimensions, including Accuracy, Completeness, Consistency, Timeliness, Uniqueness, Validity, and Integrity.
- Operate and maintain an automated data quality monitoring framework covering at least 90% of critical datasets, while developing dashboards, scorecards, and key performance indicators (KPIs) for reporting to the Data Governance Committee.
- Manage the end-to-end data quality issue lifecycle, including detection, classification, assignment, remediation, tracking, and closure, ensuring adherence to Service Level Agreements (SLAs) with a compliance target of at least 95%.
- Lead root cause analysis for recurring data quality issues and collaborate with technical data custodians and source system owners to resolve problems at their origin.
- Support data custodians across government entities by promoting the adoption of data quality standards through structured training programs, workshops, and awareness initiatives.
- Validate the creation and maintenance of Golden Records within the MDM platform by ensuring compliance with defined Match and Survivorship Rules prior to data publication through APIs.
- Document and maintain end-to-end data lineage for all evaluated datasets, ensuring complete coverage and audit readiness while supporting compliance and governance requirements.
- Contribute to the development and ongoing maintenance of the Business Glossary, data quality rule repository, and associated metadata, ensuring alignment with the program’s strategic objectives.
- Prepare and present monthly data quality reports to the Steering Committee, including key insights, trends, remediation status, and the monitoring of the Data Trust Index.
Training, Professional Certifications, and Experience Requirements
- Minimum of 5 years of professional experience in Data Quality Management, Data Governance, or a related field.
- Proven experience in data cleansing, data validation, and maintaining data accuracy, consistency, and integrity across enterprise systems.
- Strong expertise in data quality frameworks, methodologies, and best practices, including the design, implementation, and monitoring of data quality controls.
- Hands-on experience with Master Data Management (MDM) concepts, processes, and platforms, including the management of Golden Records, data matching, and survivorship rules.
- Relevant professional certifications in Data Quality, Data Governance, Master Data Management, or related disciplines (preferred), such as DAMA Certified Data Management Professional (CDMP) or equivalent industry-recognized certifications.
- **Scientific Specialization:** Bachelor's degree in Computer Science, Data Management, Data Engineering, Information Systems, or a related discipline.
- **Total Experience:** 5–7 years of overall professional experience.
- **Relevant Experience:** 4–6 years of hands-on experience in Data Engineering, Data Quality Management, Data Governance, Master Data Management (MDM), or related data management functions.
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