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Manager - Data Quality Control & Readiness

Qiddiya Investment Company

Riyadh, Riyadh Province, Saudi Arabia permanent

Posted: January 11, 2026

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Job Description

Qiddiya Investment Company is looking for an experienced and detail-oriented Manager - Data Quality to ensure the integrity and quality of data across our organization. This role is critical to maintaining the accuracy, consistency, and reliability of data used for decision-making and strategic initiatives.

Your leadership will be essential in developing data quality frameworks, implementing best practices, and collaborating with various teams to uphold data standards throughout the organization.

Key Responsibilities

• Define and implement enterprise data quality frameworks covering accuracy, completeness, consistency, timeliness, and integrity.
• Oversee data quality standards across data collection, processing, storage, analytics, AI, and reporting.
• Ensure business-generated data adheres to data quality standards from inception. Align data quality efforts with regulatory and compliance requirements.
• Implement data quality monitoring and control mechanisms at all lifecycle stages.
• Oversee data quality enforcement in AI models, data science applications, and business intelligence analytics. Drive data lineage, metadata management, and master data management (MDM) initiatives.
• Lead data quality strategies across Qiddiya’s business and technical teams.
• Establish data quality KPIs and measurement frameworks for continuous improvement.
• Work closely with IT, data engineering, analytics, and business units to embed data quality into system designs and workflows. Drive data quality automation using industry-leading tools and platforms.


Requirements:
• 8+ years of experience in data quality management, and large-scale data operations.
• Ability to align business processes with data quality standards.
• Strong understanding of data quality enforcement for AI, machine learning models, and data analytics.
• Experience with enterprise data governance tools.
• Proficiency in data validation, cleansing, and enrichment techniques. Expertise in data lifecycle management ensuring quality.

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