Role Description The Data Quality Analyst will support the monitoring, assessment, and improvement of data accuracy, completeness, consistency, reliability, and usability across business systems and reporting environments. The role focuses on identifying data quality issues, investigating root causes, maintaining data standards, and supporting initiatives that improve the overall reliability of organizational data.

Key responsibilities include reviewing datasets, conducting data validation checks, identifying inconsistencies, detecting duplicate or incomplete records, and documenting data quality issues. The role will work with structured data from databases, spreadsheets, applications, reporting systems, and other approved business sources.

The position will develop and execute data quality checks based on established rules and business requirements. Responsibilities may include comparing datasets, validating data formats, reviewing missing values, monitoring data integrity, and preparing reports that highlight data quality trends, exceptions, and areas requiring attention.

The Data Quality Analyst will collaborate with data, technology, operations, finance, compliance, and business teams to investigate data issues and identify potential root causes. The role may assist with corrective actions, data cleansing activities, process improvements, and the implementation of controls designed to prevent recurring data quality problems.

Additional responsibilities include maintaining data quality documentation, updating validation rules, supporting data governance initiatives,



tracking remediation activities, and monitoring key data quality indicators. The role may also contribute to defining data standards, business rules, quality thresholds, and procedures for maintaining reliable information.

The successful candidate should be highly detail-oriented, analytical, and comfortable working with large amounts of information. Strong problem-solving abilities are significant for identifying relationships between data issues and underlying processes, while clear communication skills are essential for explaining findings to technical and non-technical stakeholders.

Qualifications

- Bachelor’s degree, diploma, or equivalent qualification in Data Analytics, Information Technology, Computer Science, Statistics, Mathematics, Business Analytics, or a related field.
- Strong understanding of data quality concepts, including accuracy, completeness, consistency, validity, uniqueness, and timeliness.
- Familiarity with data validation, data cleansing, data profiling, reconciliation, and quality monitoring processes.
- Basic to intermediate knowledge of SQL and relational database concepts.
- Strong proficiency with Microsoft Excel, Google Sheets,



or similar data management tools.
- Familiarity with data visualization and reporting tools such as Power BI, Tableau, Looker, or equivalent platforms.
- Understanding of databases, data structures, tables, fields, relationships, and common data formats.
- Ability to identify missing, duplicated, inconsistent, invalid, or inaccurate data.
- Strong analytical and investigative skills with the ability to identify potential root causes of data quality issues.
- Ability to develop, document, and execute data quality rules, validation checks, and control procedures.
- Strong attention to detail when reviewing large datasets and investigating data discrepancies.
- Ability to prepare clear data quality reports, dashboards, summaries, and recommendations.
- Familiarity with data governance principles, metadata, data standards, and information management practices.
- Understanding of data privacy, confidentiality, security, and responsible data-handling principles.
- Ability to communicate data-related findings clearly to technical and business stakeholders.
- Strong organizational skills with the ability to track multiple data issues, remediation activities, and priorities.
- Ability to collaborate effectively with data engineers, analysts, developers, business teams, and process owners.
- Familiarity with Python, R, or other data analysis tools is advantageous.
- Proactive mindset with a strong interest in improving data reliability, business processes, and decision-making.

📌 Data Quality Analyst (Australia)
🏢 INTERNATIONAL JOB VACANCIES
📍 Australia