Data Quality Assurance
Posted Updated
- Perform basic functional software testing (black-box testing, end-to-end user scenario validation) to ensure application features operate correctly alongside data integration.
- Map acceptance criteria and design data quality rules (null constraints, uniqueness, column validity) across multi-table datasets.
- Write complex SQL queries and Python scripts to execute automated data validation, reconciliation, and integrity checks.
- Analyze end-to-end data pipelines and verify data consistency between RDBMS databases (MySQL/PostgreSQL) and BI dashboards (QuickBI).
- Partner with Data Engineers, Data Analysts, and Product Owners to identify data anomalies, perform root-cause analysis, and enforce data quality standards.
- Basic-to-intermediate knowledge of functional testing (creating test scenarios, manual/automation testing and reporting defects/bugs for end-to-end user flows).
- Strong proficiency in complex SQL (MySQL, PostgreSQL) for data validation, multi-table reconciliation (e.g., mapping and checking 5+ tables simultaneously), null/uniqueness handling, and window functions
- Proficient in Python for data manipulation and test automation.
- Strong understanding of data quality criteria, establishing Data Quality Rules, and data pipeline (ETL/ELT) workflows.
- Familiarity with Business Intelligence tools such as QuickBI (or similar) to validate data accuracy on dashboards
- Experience in development software process, preferably in Health sectors is a plus.
- Able to work from office (WFO Bandung).