Data Quality Expert

Giza Arabia; Riyadh; On-site; SAR 262,000 - 375,000; Full time

Job summary

A data solutions company located in Riyadh is seeking a professional to develop and implement enterprise-level data quality standards. The successful candidate will oversee data quality assessments, collaborate with stakeholders to establish metrics, and monitor performance. Proven expertise in data quality frameworks, SQL, and tools like Collibra is essential for this role.

Qualifications

• Deep understanding of frameworks for data quality assessment, monitoring, and improvement.
• Proficiency with data profiling, auditing, and lineage tracking tools.
• Ability to identify, analyze, and resolve underlying causes of data quality issues.
• Expertise in designing and implementing data cleansing, standardization, and enrichment processes.
• Strong command of SQL and possibly Python or R.
• Familiarity with governance frameworks and regulatory standards.
• Experience with ETL/ELT tools for data quality integration.
• Skill in defining and tracking data quality metrics and KPIs.
• Excellent communication and interpersonal skills.
• Commitment to staying updated with industry trends and best practices.

Responsibilities

• Develop and lead the implementation of data quality standards.
• Oversee data quality assessments and audits.
• Collaborate with stakeholders to establish data quality metrics.
• Design and implement data cleansing and validation strategies.
• Monitor and report on data quality performance.
• Evaluate and integrate data quality tools and technologies.
• Provide guidance and training on data quality best practices.
• Lead cross-functional initiatives for data quality improvement.
• Ensure alignment of data quality efforts with business objectives.
• Stay updated with industry trends and regulatory requirements.

Skills

Data Quality Frameworks and Standards

Data Profiling and Assessment Tools

Root Cause Analysis

Data Cleansing and Enrichment

SQL and Scripting Languages

Data Governance and Compliance

ETL/ELT Processes

Performance Measurement

Communication and Collaboration

Continuous Improvement Mindset

Tools

Collibra

Informatica Data Quality

Job description

Job Description:

1. Develop and lead the implementation of enterprise-level data quality standards, policies, and procedures.
2. Oversee data quality assessments, audits, and profiling to identify issues, root causes, and improvement opportunities.
3. Collaborate with data stewards, data architects, and business stakeholders to establish data quality metrics and KPIs.
4. Design and implement robust data cleansing, enrichment, and validation strategies across diverse data sources and platforms.
5. Monitor and report on data quality performance, ensuring transparency and accountability throughout the organization.
6. Evaluate and integrate data quality tools, technologies, and automation solutions to enhance efficiency and accuracy.
7. Provide expert guidance and training to teams on data quality best practices, methodologies, and regulatory compliance.
8. Lead cross-functional initiatives to address complex data quality challenges and drive continuous improvement.
9. Ensure alignment of data quality efforts with overall data governance and business objectives.
10. Stay current with industry trends, emerging technologies, and evolving regulatory requirements to maintain excellence in data quality practices.

Skills

• Data Quality Frameworks and Standards: Deep understanding of frameworks for data quality assessment, monitoring, and improvement.
• Data Profiling and Assessment Tools: Proficiency with data profiling, auditing, and lineage tracking tools (e.g., Collibra, Informatica Data Quality).
• Root Cause Analysis: Ability to identify, analyze, and resolve underlying causes of data quality issues.
• Data Cleansing and Enrichment: Expertise in designing and implementing data cleansing, standardization, and enrichment processes.
• SQL and Scripting Languages: Strong command of SQL and possibly Python or R to query, analyze, and transform data.
• Data Governance and Compliance: Familiarity with governance frameworks, regulatory standards (e.g., GDPR, CCPA), and compliance best practices.
• ETL/ELT Processes: Experience with ETL/ELT tools and techniques to integrate and maintain data quality in data pipelines.
• Performance Measurement: Skill in defining and tracking data quality metrics, KPIs, and performance dashboards.
• Communication and Collaboration: Excellent communication and interpersonal skills to work effectively with stakeholders, data stewards, and technical teams.
• Continuous Improvement Mindset: Commitment to staying updated with industry trends, best practices, and emerging technologies to continually enhance data quality initiatives.