Senior Test Engineer

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

It's fun to work in a company where people truly BELIEVE in what they are doing! We're committed to bringing passion and customer focus to the business.

Role Summary Mandatory: SQL, Data Validation, ETL/Data Pipeline Testing, Test Strategy & Planning, Test Case Design, Data Analytics, Automation Testing, Stakeholder Collaboration, Defect Management.

Key Responsibilities

Test Strategy & Planning

• Define and implement comprehensive test strategies for data engineering and analytics solutions.
• Develop test plans, test approaches, and validation frameworks aligned with project objectives and business requirements.
• Identify testing scope, risks, dependencies, and mitigation plans.
• Ensure appropriate test coverage across functional, integration, system, regression, and data validation testing.

Test Design & Execution

• Analyze business requirements and data specifications to create detailed test scenarios and test cases.
• Execute functional, integration, regression, and user acceptance support testing activities.
• Validate data transformations, calculations, aggregations, and business rules across data pipelines.
• Ensure testing activities align with defined quality standards and acceptance criteria.

Data Validation & Analytics Testing

• Perform extensive SQL-based data validation and reconciliation across source and target systems.
• Validate data accuracy, completeness, consistency, and integrity throughout the data lifecycle.
• Verify KPIs, metrics, reports, dashboards, and analytical outputs against business expectations.
• Analyze large datasets to identify anomalies, inconsistencies, and quality issues.

ETL/Data Pipeline Testing

• Test end-to-end ETL and ELT processes across data ingestion, transformation, and consumption layers.
• Validate data movement across multiple systems and platforms.
• Ensure data pipelines process information according to defined business and technical requirements.
• Test error-handling, exception management, and data recovery scenarios.

Defect Management & Root Cause Analysis

• Identify, document, track, and manage defects throughout the testing lifecycle.
• Perform detailed root cause analysis for data discrepancies and functional issues.
• Collaborate with development and data engineering teams to resolve defects efficiently.
• Verify fixes and support regression testing activities.

Automation & Continuous Improvement

• Identify opportunities to automate repetitive testing and data validation activities.
• Contribute to the development and maintenance of automated test suites and validation frameworks.
• Recommend improvements to testing processes, methodologies, and tools to increase efficiency and coverage.
• Support quality engineering best practices and continuous testing initiatives.

Stakeholder Collaboration

• Work closely with Business Analysts, Data Engineers, Product Owners, and business users to understand requirements and expected outcomes.
• Participate in requirement reviews, solution discussions, and testing workshops.
• Communicate testing progress, risks, defects, and quality metrics to stakeholders.
• Support user acceptance testing and production readiness activities.

At Fractal, towards our goal of “powering every human decision in the enterprise”, our partnerships and alliances help in creating and delivering a compelling suite of solutions to unlock value. We partner with companies from around the globe, leaders in their respective fields. With Fractal’s expertise in artificial intelligence, design, engineering, and digital transformation, combined with the data, technology, and software platforms from our partners, we create cutting-edge solutions to problems in the business world. We understand how critical and timely decision triggers, and information, empower our clients to create, unlock, deliver, and realize value. Together with our partners, our goal is to serve each client in their end-to-end data-to-decision journey.