Role Overview
We are looking for a Senior Data Quality Engineer to drive enterprise data quality across data platforms and lakehouse environments. The role will be responsible for designing and implementing automated data quality controls, monitoring data quality, performing root-cause analysis, and ensuring data is accurate, complete, consistent, and reliable for reporting, analytics, and AI.
The role will work closely with Data Owners, Data Stewards, and Data Engineering teams, using Microsoft Purview and MDM capabilities for governance and data quality management.
Key Responsibilities
- Define, implement, and maintain an enterprise Data Quality framework, including DQ dimensions, KPIs, thresholds, standards, and controls.
- Perform data profiling and baseline assessments to identify data quality issues.
- Design and implement automated DQ checks across Bronze, Silver, Gold, and analytical layers.
- Build data validation, rejection, quarantine, exception-handling, and remediation controls within data pipelines.
- Implement source-to-target reconciliation to validate completeness, accuracy, and consistency.
- Monitor data quality across accuracy, completeness, validity, consistency, uniqueness, timeliness, and referential integrity.
- Perform root-cause analysis of data quality issues and coordinate remediation with Data Engineers, Data Owners, and source-system teams.
- Translate business rules and requirements into executable technical data quality controls.
- Support Microsoft Purview and MDM initiatives, including Critical Data Elements, DQ scoring, duplicate detection, reference data validation, and golden-record quality.
- Maintain traceability between DQ rules, business requirements, metadata, data models, and source-to-target mappings.
- Support knowledge transfer and coach Data Owners and Data Stewards on data quality practices and tools.
Required Skills & Experience
- 4+ years of experience in Data Quality, Data Engineering, Data Management, or Data Governance.
- Hands-on experience with data profiling, DQ rules, validation, reconciliation, monitoring, and remediation.
- Strong Advanced SQL skills.
- Practical experience with Python, PySpark, or Spark.
- Strong understanding of relational and dimensional data modelling.
- Knowledge of business/surrogate keys, normalization, referential integrity, and Slowly Changing Dimensions (SCD).
- Experience with cloud data platforms and Lakehouse/Medallion architecture.
- Experience with Azure / Microsoft Fabric is preferred.
- Working knowledge of Microsoft Purview and MDM platforms.
- Familiarity with UAE PDPL, Dubai Data Law, and DESC ISR is preferred.
- Excellent English communication and stakeholder-management skills.
- Arabic proficiency is an advantage.
Key Skills
Data Quality | Advanced SQL | Python/PySpark | Azure | Microsoft Fabric | Lakehouse | Medallion Architecture | Microsoft Purview | MDM | Data Governance | Data Profiling | Data Reconciliation
