Data Quality Analyst

Hands-on ability to work with datasets using SQL, Excel, BI tools, or equivalent analysis tools
Basic working knowledge of data profiling and data validation techniques
Understanding of common data quality issues such as missing values, invalid values, duplicates, inconsistencies, outdated records, and non-standard formats
Basic working knowledge of data quality dimensions such as completeness, validity, consistency, uniqueness, timeliness, accuracy, and conformity
Ability to compare datasets, prepare samples, identify exceptions, and summarize observations
Ability to document findings clearly using structured templates, tables, issue logs, and evidence packs
Basic understanding of business rules, data rules, reference data, and valid value lists
Working knowledge of Excel functions, filters, pivots, lookups, and data preparation techniques
Basic SQL capability, including filtering, joins, grouping, counts, duplicates, null checks, and simple validations
Ability to support report validation, dashboard checking, data extract comparison, and testing support
Good attention to detail when reviewing data values, formats, counts, and patterns
Ability to escalate unclear findings and ask the right clarification questions
Willingness to learn data governance, metadata, data lifecycle, and data management concepts

Perform data profiling and data analysis using agreed methods and tools
Identify missing, invalid, duplicate, inconsistent, incomplete, outdated, or non-standard data
Prepare data samples, exception lists, issue summaries, and profiling outputs
Document data quality findings in a clear and structured way
Support rule documentation, data validation, and evidence preparation
Maintain issue logs, analysis files, rule trackers, and exception registers
Support data reconciliation and comparison activities
Support validation of reports, dashboards, scorecards, and data extracts
Support testing, retesting, and defect investigation where data evidence is required
Escalate unclear findings, unusual patterns, and potential issue drivers to senior team members
Support workshops and review sessions by preparing analysis materials
Contribute to documentation, knowledge transfer, and continuous improvement activities

The Data Quality Analyst is a hands-on analytical role. It is focused on finding, documenting, and validating data quality issues. The role is a strong development path toward Senior Data Quality Analyst, Data Quality Lead, Data Governance Analyst, or Data Analyst roles.

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.

2–3 years of experience in data analysis, reporting, data profiling, data quality, business intelligence, data migration, data validation, or data-related projects.

Fresh graduates with strong analytical, SQL, Excel, statistics, or data skills may be considered for junior roles.

Preferred certifications include:

DAMA CDMP Associate or Data Management Fundamentals training
SQL, analytics, BI, or data visualization certification
Microsoft, Google, AWS, Snowflake, Databricks, or equivalent foundational data certification where relevant
Informatica Data Quality / IDMC foundational certification where relevant
Business analysis or analytics foundation certification where relevant