Requirements
Requires 4+ years of experience in Data Quality, Data Engineering, Data Management, or Data Governance. Must have strong hands-on experience in Data Profiling, Data Quality Rules, Data Validation, Reconciliation, Monitoring, and Remediation. Advanced SQL skills with practical experience in Python, PySpark, Spark, or equivalent technologies are essential, along with a strong understanding of relational and dimensional data modeling, and experience with Cloud Data Platforms and Lakehouse/Medallion Architecture. Strong analytical, problem-solving, documentation, communication, and stakeholder-management skills are also required.
Description
Senior Data Quality Engineer – EmiratizationLocation: Dubai, UAEEmployment Type: Full-TimeIndustry: Government / Public SectorThis is an Emiratization opportunity. UAE Nationals are encouraged to apply. Arabic-speaking candidates are strongly preferred.About the RoleWe are looking for a Senior Data Quality Engineer to drive enterprise-wide data quality and ensure trusted, accurate, and reliable data for analytics and reporting with a leading Government entity in Dubai.The ideal candidate will have strong hands-on experience in Data Quality Engineering, Data Profiling, SQL, Python/PySpark, Data Reconciliation, Automated Data Quality Controls, Cloud Data Platforms, Lakehouse/Medallion Architecture, Metadata Management, and Data Governance.Key ResponsibilitiesDefine and maintain Enterprise Data Quality Frameworks, standards, KPIs, thresholds, dimensions, and controls.Conduct data profiling, data-quality assessments, and source-data analysis.Design and implement automated data-quality checks across ingestion, transformation, curated, and analytical layers.Develop validation, rejection/quarantine, exception-handling, and remediation rules within data pipelines.Build source-to-target reconciliation controls and monitor data completeness, accuracy, and consistency.Monitor DQ dimensions including accuracy, completeness, validity, consistency, uniqueness, timeliness, and referential integrity.Investigate data-quality issues, conduct root-cause analysis, and drive remediation with Data Engineers, Data Owners, and technical teams.Translate business rules, keys, reference data, constraints, and historical requirements into technical data-quality controls.Support Microsoft Purview and MDM platforms such as Profisee, including Critical Data Elements (CDEs), duplicate detection, master/reference data validation, and golden-record quality.Maintain traceability between DQ rules, business requirements, metadata, data models, and source-to-target mappings.Required Skills & Experience4+ years of experience in Data Quality, Data Engineering, Data Management, or Data Governance.Strong hands-on experience in Data Profiling, Data Quality Rules, Data Validation, Reconciliation, Monitoring, and Remediation.Advanced SQL skills with practical experience in Python, PySpark, Spark, or equivalent technologies.Strong understanding of relational and dimensional data modelling, business/surrogate keys, normalization, referential integrity, and Slowly Changing Dimensions (SCD).Experience with Cloud Data Platforms and Lakehouse/Medallion Architecture.Strong analytical, problem-solving, documentation, communication, and stakeholder-management skills.Please Note: Due to the high volume of applications, only shortlisted candidates will be contacted. We appreciate your understanding.If this opportunity excites you and your experience matches the above requirements, we encourage you to apply.