Data Quality Engineer

Company Description

At Devoteam, we believe that technology, combined with strong human values, can
actively drive change for the better. Discover how Tech for People is shaping the future,
creating a positive impact on individuals and the world around us.

With over 25 years of passion for technology and a presence in 18+ countries across EMEA and beyond, we are committed to leveraging innovation, expertise, and human-centric values to make a difference.

Job Description

We are seeking a highly skilled Data Quality Engineer to play a key role in designing, implementing, and maintaining data quality frameworks that support our clients' data and analytics initiatives. The ideal candidate combines strong technical expertise in data quality management with the ability to understand business processes and translate requirements into scalable, maintainable, and governed data quality solutions.
You will work closely with data architects, data engineers, business analysts, data governance teams, and business stakeholders to define data quality requirements, establish validation standards, and implement controls that ensure data accuracy, completeness, consistency, and reliability across enterprise data platforms.


Key Responsibilities:

• Collaborate with business stakeholders, data architects, governance teams, and data engineers to gather and analyze data quality requirements.
• Design, develop, and maintain data quality frameworks, validation rules, and monitoring processes across enterprise data assets.
• Profile and analyze data sources to identify quality issues, anomalies, patterns, and improvement opportunities.
• Define, implement, and maintain data quality rules across key dimensions including completeness, accuracy, consistency, uniqueness, validity, and timeliness.
• Translate business requirements and critical data elements (CDEs) into measurable and actionable data quality controls.
• Design and implement automated data validation, reconciliation, and monitoring processes.
• Work closely with data integration and engineering teams to embed data quality controls within data pipelines and transformation processes.
• Support data governance initiatives through metadata management, data lineage documentation, data cataloging, and quality reporting.
• Monitor data quality performance indicators and investigate root causes of recurring data quality issues.
• Collaborate with business and technical teams to identify remediation actions and continuous improvement opportunities.
• Ensure compliance with organizational data governance standards, regulatory requirements, and industry best practices.
• Support data warehousing, reporting, and analytics initiatives by ensuring the availability of trusted and high-quality data assets.
• Participate in solution reviews and promote best practices related to data quality management and governance.
• Document data quality rules, validation logic, data flows, issue management processes, and technical specifications.

Qualifications

Required Qualifications:

• Bachelor's degree in Computer Science, Information Systems, Data Management, Engineering, or a related field.
• Minimum 2 years of hands-on experience in data quality, data engineering, data governance, or related data management disciplines.

Preferred Qualifications:

• Experience with enterprise data quality and data integration platforms such as Informatica IDMC, IICS, PowerCenter, and Informatica Data Quality (IDQ).
• Familiarity with data cataloging, metadata management, and data governance platforms.
• Experience working within regulated environments and familiarity with Saudi NDMO and NDI requirements.
• Experience implementing data quality KPIs, scorecards, and monitoring dashboards.
• Familiarity with REST APIs, data ingestion frameworks, and modern cloud data platforms.
• Experience supporting CI/CD practices and deployment processes within data environments.

What We Are Looking For:
We are looking for someone who is passionate about improving data trust and reliability across the organization. The ideal candidate proactively identifies data quality risks, challenges assumptions, investigates root causes, and collaborates effectively with both business and technical teams to ensure that data remains accurate, consistent, governed, and fit for purpose.

Additional Information

Fluency in Arabic & English is highly desirable