Senior Test Engineer — Data Quality & ETL Automation

Fractal Analytics Inc.; Hinoba-an; On-site; PHP 600,000 - 800,000; Full time

Job summary

Fractal Analytics Inc. is seeking a QA engineer focused on data testing to ensure data quality across pipelines and analytics outputs.

You will design test strategies, validate data accuracy, and collaborate with data engineers and analysts to verify KPIs and dashboards, enabling reliable insights for business users.

This role emphasizes SQL-based validation, ETL/ELT testing, and automation to support scalable, accurate analytics. Collaboration and continuous improvement are essential.

Qualifications

• Experience with SQL-based data validation and data pipeline testing.
• Ability to design test strategies, plans, and test cases for data analytics projects.
• Strong collaboration with stakeholders and defect management.

Responsibilities

• Define and implement test strategies for data engineering and analytics solutions.
• Develop test plans, validation frameworks, and risk mitigation plans.
• Identify scope, dependencies, and ensure test coverage across functional, integration, system, and data validation tests.
• Analyze business requirements to create test scenarios and cases.
• Execute functional, integration, regression, and UAT support testing.
• Validate data transformations, calculations, and business rules across pipelines.
• Test end-to-end ETL/ELT processes and data movement across systems.
• Perform defect management and root cause analysis with teams.
• Contribute to automation and continuous improvement of testing processes.

Skills

SQL

Data Validation

ETL Testing

Data Pipeline Testing

Test Strategy

Test Planning

Test Case Design

Data Analytics

Automation Testing

Stakeholder Collaboration

Defect Management

Job description

Fractal Analytics Inc. is seeking a QA engineer focused on data testing to ensure data quality across pipelines and analytics outputs.

You will design test strategies, validate data accuracy, and collaborate with data engineers and analysts to verify KPIs and dashboards, enabling reliable insights for business users.

This role emphasizes SQL-based validation, ETL/ELT testing, and automation to support scalable, accurate analytics. Collaboration and continuous improvement are essential.