QA Lead

GCash; Philippines; On-site; PHP 1,200,000 - 2,300,000; Full time

Benefits offered by this job

Career growth

Competitive compensation

Flexible benefits

Job summary

GCash, the leading fintech in the Philippines, is seeking a QA Lead to drive data QA across analytics and data warehousing environments. You will design test plans, validate data outputs, and coordinate with Data Analysts and DAISMs to ensure quality and timely delivery.

You will leverage SQL-based validation, BI tools, and data QA automation to improve accuracy and efficiency while maintaining audit trails and SLAs in a fast-paced fintech setting.

Qualifications

• Experience in Quality Assurance / Data Testing in analytics, data warehousing, or data platform environments.
• Strong SQL skills for validating data across data layers and building ad hoc validation queries.
• Experience with BI and reporting tools (Looker Studio, Google Data Studio, Google Sheets, Excel; familiarity with BigQuery, Tableau, Power BI).

Responsibilities

• Create detailed test cases, test plans, and QA checklists based on requirements and acceptance criteria.
• Perform data quality validation and QA testing on outputs (reports, dashboards, tables).
• Execute SQL-based validation across data layers to ensure alignment with requirements.
• Coordinate with Data Analysts and DAISMs to clarify requirements and acceptance criteria.
• Conduct QA testing within SLA timelines and document defects in Jira, with retesting and sign-off.
• Maintain QA documentation and artifacts for auditability and reuse.
• Participate in daily stand-ups and sprint activities to report QA progress and blockers.
• Leverage AI and automation to improve QA activities while ensuring traceability and data integrity.

Skills

QA testing concepts

SQL

Data validation

Analytics

Agile / Scrum

Tools

Google Data Studio/Looker Studio

BigQuery

Tableau

Power BI

Google Sheets

Excel

Jira

Confluence

Job description

QA Lead# Careers## QA LeadApply: NCR - WCC: Full time: Posted Yesterday: R0000021921Do you want to take the first step in making Filipinos’ lives better everyday? Here in GCash we want to stay at the forefront of the FinTech industry by creating innovative, meaningful, and convenient financial solutions for the nation! G ka ba? Join the G Nation today!**You will be responsible for the following:**I. Creates detailed test cases, test plans, and QA checklists based on business requirements, user stories, and acceptance criteria to ensure outputs meet defined expectations. II. Performs data quality validation and QA testing on analytical outputs such as ad hoc extracts, reports, dashboards, tables, and views to ensure completeness, accuracy, consistency, uniqueness, and fitness for use. III. Executes SQL-based validation and testing across relevant data layers and environments to confirm that outputs align with business and technical requirements. IV. Coordinates with Data Analysts, DAISMs (Data and AI Success Manager) and other stakeholders to clarify requirements, define test coverage, and align on acceptance criteria, scope, and timelines. V. Conducts QA testing within agreed SLA timelines and ensures timely completion of assigned requests without compromising quality. VI. Logs, tracks, and supports resolution of defects by documenting findings, coordinating triage, validating fixes, and performing retesting prior to sign-off VII. Provides QA sign-off and validation support for UAT by ensuring outputs have passed required quality checks before endorsement for requestor acceptance or production deployment.VIII. Maintains QA documentation and testing artifacts such as test scripts, evidence files, validation queries, checklists, and traceability records for audibility and future reuse. IX. Participates in team ceremonies and status discussions such as daily stand-ups and sprint activities to report QA progress, risks, blockers, and testing updates. X. Leverage AI and automation to improve BA-QA activities - including test-case generation, data validation, regression testing, defect analysis, and QA reporting while ensuring human oversight, traceability, data integrity, and compliance with established standards. B. Displays (*The Knowledge, Skills, and Behaviors indicating how tasks / responsibilities will be performed*) I. Detail orientation in identifying test cases/scenarios and spotting data issues such as duplicates, missing values, inconsistencies, and logic gaps. II. Strong grounding in QA concepts and methodologies including test design, defect management, validation, and sign-off practices. III. Analytical and problem-solving skills to investigate data issues, trace root causes, and recommend resolutions. IV. Knowledge of analytics and data warehousing concepts to effectively validate outputs and understand data flow dependencies. V. Strong collaboration and communication skills to work effectively with Data Analysts, DAISM (Data and AI Success Manager), business teams, and other stakeholders. VI. Agile mindset with a “fast fail, learn fast” attitude in a fast-paced and iterative work environment. C. Delivers (*The specific outputs / tangible results produced by the role; resources responsible for*) I. Test cases, test plans, and QA checklists that validate whether data outputs meet defined business requirements and acceptance criteria. II. QA evidence and data quality validation results, including queries, screenshots, and supporting documentation that demonstrate completeness, accuracy, and readiness for UAT or sign-off. III. Defect logs and QA reports summarizing issues found, root causes, severity, status, and retest results, with proper tracking through Jira and BA QA metrics/KPIs. IV. Improved quality of analytical outputs through early issue detection, reduced rework, and stronger compliance with SLA and QA standards. KPIsD. SLA complianceE. Peer review coverage and effectivenessF. Stakeholder feedback on QA supportG. Business support efficiency (throughput, QA cycle time)H. Quality of output (defect leakage, rework) **We are looking for:*** Experience in Quality Assurance / Data Testing (QA testing, concepts, methodologies) preferably in analytics, data warehousing, or data platform environments.* Strong SQL skills (required) for validating data across data layers and building ad hoc validation queries.* Hands-on experience with BI and reporting tools such as Google Data Studio / Looker Studio, Google Sheets, Excel; familiarity with BigQuery, Tableau, Power BI, and DAAS is preferred.* Experience with big data technologies (e.g., Hadoop / big data stacks) is an advantage.* Experience using Jira and Confluence (or similar tools) for ticketing, defect tracking, and documentation is preferred.* Experience with data test / data QA automation (e.g., SQL-based regression suites, scheduled validation jobs, or similar data QA automation tools) is an advantage.* Prior experience in financial services, fintech, or large-scale transaction data environments is an advantage.**What We Offer**Opportunity for career growth and development in the #1 FinTech company in the country Working with a dynamic and highly collaborative team who want to change the game A company that values their people with highly competitive and flexible compensation and benefits package