Senior Data Quality Engineer (Automation)

IntroductionDigiEx Group is a global technology partner specializing in Innovation Software Development, AI-powered solutions, Tech Talent services, and Digital Transformation. Headquartered in Vietnam, DigiEx helps startups and enterprises worldwide build scalable digital products and high-performing engineering teams.
At DigiEx, we embrace an AI-first engineering culture, empowering every team member to leverage AI technologies to build smarter software, improve productivity, and continuously innovate.
Key Responsibilities
Own the data quality and test automation strategy across ETL pipelines, data warehouses, and downstream reporting within client engagements.
Design, develop, and maintain automated and manual validation suites covering data transformations, integrity, completeness, and reconciliation.
Define and enforce data quality standards and SLAs, establishing validation rules and quality thresholds before pipelines go live.
Lead QA gates for data and reporting releases, ensuring data meets quality standards before reaching production dashboards or operational workflows.
Validate data mappings and transformations across source systems, ETL processes, and target data platforms.
Lead root-cause analysis and defect resolution for data discrepancies, ensuring issues are clearly documented and tracked through remediation.
Build and maintain automated regression coverage for reporting workflows, dashboards, campaign reporting, and operational data feeds.
Drive improvements to QA automation frameworks, testing standards, and data governance practices across the engagement.
RequirementsMust Have
Bachelor's degree or higher in Computer Science, Information Technology, Information Systems, or a related field.
5+ years of experience in Data QA, Data Testing, or Data Engineering, with strong hands-on experience in data pipeline testing and automation.
Strong SQL skills for complex data validation, reconciliation, and integrity checks across large-scale datasets.
Hands-on experience with ETL testing and validating data transformations in Snowflake, Redshift, BigQuery, or equivalent platforms.
Strong experience with data test automation, using dbt Tests, Great Expectations, pytest, or equivalent frameworks.
Experience designing and implementing QA strategies, regression coverage, and automated quality gates for data platforms.
Strong analytical and root-cause analysis skills, with the ability to distinguish data quality issues from business logic or source-system issues.
Experience with Jira or equivalent defect management tools, including clear documentation, impact assessment, and remediation tracking.
Ability to review AI-generated data pipeline code and transformation logic, identifying correctness, integrity, security, and quality issues.
Good understanding of data governance, PII handling, and compliance in regulated environments.
Business-level English, with the ability to communicate testing results, defects, and release readiness with technical and client stakeholders.
Nice to Have
Experience in healthcare, pharmaceutical, or life sciences data environments.
Experience integrating automated data testing into CI/CD pipelines, using dbt Cloud, Airflow, or equivalent tools.
Familiarity with Tableau, Power BI, or other BI platforms and validating dashboard metrics against source data.
Knowledge of HIPAA, SOC 2, or similar compliance requirements.
Contact:
Phone/ Whatsapp/ Zalo: (+84)703085346 (Ms. Trinh)