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Data Engineer

Devoteam InternationalRiyadh, KSA1 months agoSeniorfulltime
Data EngineeringData QualityETLData GovernanceData PipelinesSQLPythonData WarehousingData ModelingMDM
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Via NaukriGulf·

About This Role

Design, implement, and maintain data quality frameworks, rules, and processes to ensure the accuracy, completeness, and reliability of enterprise data.
Collaborate with data governance, MDM, and data integration teams to enforce consistent data quality standards across systems.
Conduct data profiling, anomaly detection, and validation to identify quality gaps and root causes.
Develop automated data quality checks and workflows for continuous monitoring and remediation.
Define and manage key data quality metrics (DQ KPIs) and build dashboards to visualize performance trends.
Document data quality rules, issue logs, and remediation actions as part of the data governance framework.
Work closely with business data stewards and domain owners to define data quality expectations and acceptance thresholds.
Support audits, compliance reviews, and data management maturity assessments by providing DQ evidence and reports.
Lead the design and deployment of scalable data quality solutions across multiple data domains and systems.
Define enterprise data quality standards, policies, and rule frameworks aligned with governance strategy.
Establish data quality scorecards, thresholds, and escalation workflows for high-impact issues.
Conduct root cause analysis and lead remediation programs for chronic data issues.
Mentor junior engineers and promote data quality best practices across teams.
Participate in compliance with the local data management regulations (e.g. NDMO, NDI).
Design, build, and maintain scalable, secure, and robust data pipelines for efficient data ingestion and transformation, with a strong focus on building quality checks into the infrastructure itself.
Collaborate with cross-functional and leadership teams (Data Scientists, Analysts, and Business Leaders) to translate complex business requirements into technical data quality solutions.
Research, evaluate, and recommend new data quality tools, technologies, and practices to enhance the reliability, security, and scalability of the data infrastructure.

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