Data Quality Expert

Key Accountabilities

• Enterprise Data Quality Framework established and adopted across all business units.

• Achievement of 95%+ data quality scores for critical data elements.

• Reduction in data-related incidents and issues through proactive monitoring.

• Automated Data Quality monitoring dashboards deployed for real-time visibility.

Delivery of Data Quality scorecards and KPIs aligned with business objectives.

• Successful remediation of at least 80% of identified data quality issues.

• Clear documentation of data quality standards, processes, and governance playbooks.

Key Responsibilities

• Define and implement an Enterprise Data Quality Strategy and Framework aligned with business objectives.

• Develop comprehensive Data Quality KPIs and Scorecards (completeness, timeliness, accuracy, uniqueness, integrity, consistency).

• Design and implement automated Data Quality rules, validations, and monitoring processes.

• Establish data profiling practices to identify quality issues and anomalies proactively.

• Create and maintain a Data Quality dashboard for real-time monitoring and alerting.

• Collaborate with business stakeholders and data stewards to define data standards and acceptance criteria.

• Design and implement data quality issue management workflows and remediation processes.

• Establish root cause analysis procedures for recurring data quality problems.

• Ensure compliance with PDPL and NDMO requirements for data quality and governance.

• Implement data quality controls at source systems and throughout data pipelines.

• Define and enforce data quality checkpoints across the data lifecycle.

• Document data quality processes, standards, playbooks, and stewardship guidelines.

• Lead data quality assessment initiatives and maturity evaluations.

• Provide training and awareness sessions for internal teams on data quality best practices.

• Work closely with Enterprise Data Architect to ensure quality standards are embedded in data architecture.

• Collaborate with Data Scientists and Analytics teams to ensure high-quality data feeds.

• Support the establishment of a Data Stewardship program and community of practice.

• Drive continuous improvement in data quality metrics and processes.

• Evaluate and recommend Data Quality tools and technologies.

Knowledge and Experience

• 7+ years of proven experience in data quality, data governance, or master data management.

• Strong understanding of Data Quality dimensions, metrics, and best practices.

• Hands-on experience with Data Quality tools (Informatica DQ, Talend, Ataccama, Collibra, dataplux, or cloud-native solutions).

• Experience with data profiling, cleansing, and standardization techniques.

• Expertise in SQL and data analysis for quality assessment.

• Experience with metadata management, data lineage, and stewardship processes.

• Knowledge of regulatory requirements in Saudi Arabia (PDPL, NDMO).

• Strong understanding of data governance frameworks and standards.

• Experience in designing and implementing data quality monitoring and reporting.

• Excellent stakeholder engagement and communication skills.

• Ability to translate technical data quality issues into business impact.

• Insurance or financial services domain knowledge with understanding of critical data domains.

• Experience integrating Data Quality frameworks into cloud platforms (BigQuery, Databricks, Snowflake).

• Knowledge of data catalog solutions, business glossaries, and metadata management tools.

• Experience with API data quality and real-time data validation.

• Familiarity with machine learning for anomaly detection and data quality prediction.

• Understanding of MDM (Master Data Management) concepts and implementation.

• Experience with data observability and DataOps practices.

• Knowledge of data quality in unstructured and semi-structured data contexts.

• Previous experience with SAMA/IA regulatory compliance in Saudi Arabia.

• Leadership skills to mentor analysts, data stewards, and technical teams.

• Change management experience for driving data quality culture transformation.

• Certification in Six Sigma or quality management methodologies.