Senior Data Quality Analyst

Advanced hands-on experience with SQL, data querying, data profiling, and data analysis

Strong practical understanding of data quality dimensions and how they appear in real datasets

Hands-on experience analyzing structured datasets across databases, spreadsheets, reporting extracts, data warehouses, or data lakes

Working knowledge of data validation, reconciliation, exception analysis, duplicate detection, pattern analysis, and data sampling techniques

Ability to interpret business rules and convert them into testable data conditions, validation logic, and expected outcomes

Ability to investigate data anomalies using data evidence, business context, system behavior, and process knowledge

Strong experience preparing data samples, issue evidence, exception lists, analytical summaries, and stakeholder-ready findings

Working knowledge of BI tools, reporting tools, profiling tools, data quality tools, or data catalog tools

Good understanding of source systems, transformations, data pipelines, reporting layers, and how data movement can affect quality

Ability to review analyst outputs and identify gaps in logic, evidence, completeness, or clarity

Strong Excel and data manipulation capability

Ability to explain technical data findings to non-technical business stakeholders

Good understanding of data governance, metadata, ownership, and stewardship concepts

Strong documentation skills for rule analysis, issue evidence, data observations, and validation results

Perform advanced data profiling and data quality analysis

Analyze data issues across completeness, validity, consistency, uniqueness, integrity, accuracy, timeliness, and conformity

Investigate data anomalies, trends, outliers, exceptions, and recurring issue patterns

Interpret data quality issues using business process, system, and reporting context

Examine source data, transformation logic, business rules, and process behavior to understand issue drivers

Prepare analytical evidence, data samples, exception lists, and issue summaries

Support the definition and refinement of data quality rules, thresholds, and validation logic

Validate data quality dashboards, scorecards, reports, and exception outputs

Review outputs prepared by Data Quality Analysts for accuracy, completeness, and clarity

Support business discussions by explaining findings in practical, non-technical language

Maintain data quality analysis documentation, issue registers, rule documentation, and evidence packs

Support testing, retesting, and defect investigation where data validation is required

Identify recurring issue patterns and recommend practical improvement opportunities

Support knowledge transfer and capability building for junior analysts and client teams

The Senior Data Quality Analyst is a hands-on expert role.

The role requires depth in SQL analysis, data profiling, validation, business curiosity, and the ability to move from raw data issues to clear, evidenced, and actionable findings.

Bachelor’s degree in Information Systems, Computer Science, Statistics, Mathematics, Business Analytics, Economics, Engineering, Management Information Systems, or a related discipline.

Arabic and English are mandatory.

4–7+ years of experience in data quality analysis, data profiling, SQL analysis, reporting analysis, data reconciliation, data migration, data integration, data governance, or business data analysis.

Experience working with complex datasets, business rules, exception analysis, reporting outputs, data validation, and technical/business stakeholders is preferred.

Informatica Data Quality / IDMC certification where relevant

Microsoft, AWS, Google Cloud, Snowflake, Databricks, or equivalent data platform certification where relevant

SQL, analytics, BI, or data engineering certification where relevant

Business analysis or analytics certification where relevant