Role DescriptionThe Data Quality Analyst will support the accuracy, consistency, completeness, validity, and reliability of data across business systems, databases, reports, and operational processes. The role focuses on identifying data quality issues, investigating discrepancies, maintaining data standards, and supporting initiatives that improve the overall quality and usability of organizational information.

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

The position will perform routine data quality checks based on established business rules and validation requirements. Responsibilities may include data profiling, reconciliation, format validation, completeness checks, duplicate detection, exception reporting, and monitoring data quality indicators.

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

Additional responsibilities include maintaining data quality documentation, updating validation rules, tracking remediation activities, preparing data quality reports, and supporting data governance initiatives. The role may also contribute to defining data standards, business rules, quality thresholds,



and procedures for maintaining reliable information.

The successful candidate should be analytical, detail-oriented, organized, and comfortable working with structured datasets and large volumes of information. Solid problem-solving abilities are important for investigating discrepancies and identifying relationships between data issues and underlying business processes.

The role also requires strong communication and collaboration skills, as the Data Quality Analyst will need to explain findings clearly, coordinate corrective actions, and work with different stakeholders to improve data processes and reporting reliability.

Qualifications

- Bachelor’s degree, diploma, or equivalent qualification in Data Analytics, Computer Science, Information Technology, 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 profiling, data cleansing, reconciliation, and quality monitoring processes.
- Basic to intermediate knowledge of SQL and relational database concepts.
- Proficiency with Microsoft Excel, Google Sheets, or similar spreadsheet and data-management tools.




- Familiarity with data visualization and reporting platforms such as Power BI, Tableau, Looker, or equivalent tools.
- Understanding of databases, tables, fields, relationships, data structures, and common data formats.
- Ability to identify missing, duplicated, inconsistent, inaccurate, or invalid information within datasets.
- 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 datasets, reports, records, and data-related documentation.
- Ability to prepare data quality reports, dashboards, summaries, and actionable recommendations.
- Familiarity with data governance principles, metadata, data standards, and information management practices.
- Understanding of data privacy, confidentiality, security, and responsible data-handling principles.
- Strong written and verbal communication skills with the ability to explain data issues to technical and non-technical stakeholders.
- Strong organizational and time-management skills with the ability to manage multiple data issues and remediation activities.
- Ability to collaborate effectively with data engineers, developers, analysts, business teams, and process owners.
- Familiarity with Python, R, or other data analysis technologies is advantageous.
- Proactive and detail-focused approach with a strong interest in improving data reliability, operational efficiency, and business decision-making.

📌 Data Quality Analyst (Australia)
🏢 Tekno park
📍 Australia