Data Quality Analyst / Junior Data Quality Analyst / Data Quality Specialist (Entry / Junior Level)Role Description

We are seeking a precise, analytical, and process-driven Data Quality Analyst / Junior Data Quality Analyst / Data Quality Specialist (Entry / Junior Level) to safeguard the accuracy, completeness, and integrity of our enterprise data assets. In this foundational role, you will work closely with Data Engineers, Data Analysts, Database Administrators, and Business Intelligence teams to monitor, audit, and improve data quality across core pipelines and repositories. You will be responsible for defining data validation rules, detecting anomalies or corruption, conducting root-cause investigations on pipeline errors, and executing data remediation workflows.

Responsibilities include running routine automated quality checks, auditing master data sets for duplicates or missing values, documenting data lineage and metadata catalogs, and assisting with data governance policies. Success in this position requires a keen eye for detail, strong SQL querying capabilities, basic scripting skills for data profiling, and a proactive commitment to ensuring high-quality data across all business operations.

Qualifications

- Education: Bachelor's degree or Diploma in Data Science, Computer Science, Information Systems, Statistics, Software Engineering, or a related quantitative field.
- Database & SQL Querying: Strong proficiency in writing basic-to-intermediate SQL queries (SELECT, JOIN, GROUP BY, subqueries, and string manipulation) to profile, audit, and compare datasets across relational databases (e.g.,



PostgreSQL, MySQL, SQL Server, or Snowflake).
- Data Profiling & Quality Frameworks: Practical understanding of core data quality dimensions—accuracy, completeness, consistency, timeliness, uniqueness, and validity.
- Data Cleaning & Scripting: Hands-on experience or coursework using Python (Pandas) or R for automated data cleaning, duplicate detection, pattern matching, and dataset validation.
- Data Quality & ETL Tools: Exposure to dedicated data quality, profiling, or ETL validation tools (e.g., Great Expectations, Talend, Informatica Data Quality, or AWS Glue) is an advantage.
- Spreadsheet Proficiency: Advanced skills in Microsoft Excel / Google Sheets (VLOOKUP/XLOOKUP, Pivot Tables, conditional formatting, and regular expressions) for rapid ad-hoc data profiling and discrepancy mapping.
- Root-Cause Analysis: Strong logical problem-solving ability to trace data errors back to source systems, API integrations, user input mistakes, or ETL transformation failures.
- Data Governance & Metadata: Familiarity with basic data governance principles, metadata management, data dictionary maintenance, and master data management (MDM) concepts.
- Communication & Collaboration: Excellent verbal and written communication skills to articulate technical data issues, document validation rules, and collaborate with data engineers and business stakeholders.
- Professional Attributes: Rigorous attention to detail, solid ethical standards regarding data handling, structured organizational habits, and a continuous focus on operational quality.

📌 Data Quality Analyst / Junior Data Quality Analyst / Data Quality Specialist (Entry / Junior Level) (New South Wales)
🏢 UC Exhibition
📍 New South Wales