Do 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:
Does (The tasks / responsibilities that the role performs to address requirements in Key Result Areas)
- Lead and manage the end-to-end QA function for Business Analytics outputs, ensuring that adhoc extracts, reports, dashboards, and other in-scope data deliverables meet defined business and technical requirements before endorsement to UAT or production.
- Establish, implement, and continuously improve QA strategies, processes, ways-of-working, and governance standards for Business Analytics, including test planning, sign-off criteria, documentation templates, and quality controls aligned with agreed SLAs and KPIs.
- Oversee the creation, review, and approval of detailed test cases, test plans, QA checklists, and SQL-based validation approaches based on business requirements, user stories, and acceptance criteria.
- Manage data quality validation and testing activities across Business Analytics outputs by ensuring completeness, accuracy, consistency, uniqueness, logic integrity, and readiness for business use.
- Provide leadership and direction to the QA team by assigning work, monitoring testing progress, reviewing output quality, removing blockers, and ensuring delivery of QA activities within committed timelines.
- Coordinate closely with Data Analysts, DAISMs (Data and AI Success Manager), Project Management Office, and business stakeholders to clarify requirements, align on scope and acceptance criteria, and ensure timely resolution of issues affecting quality and delivery.
- Drive defect management by ensuring timely logging, triaging, tracking, validation of fixes, retesting, and final QA endorsement of tickets prior to requestor acceptance or production deployment.
- Maintain and enforce complete QA documentation and testing artifacts, including evidence files, validation queries, sign-off records, and reusable knowledge assets, to support auditability, traceability, and future testing efficiency.
- Track, analyze, and report QA metrics and operational performance indicators such as SLA compliance, defect leakage, rework, throughput, cycle time, stakeholder feedback, and overall quality of output to management and relevant stakeholders.
- Lead continuous improvement initiatives for QA within Business Analytics by identifying quality gaps, strengthening controls, standardizing practices, and introducing automation or scalable solutions that improve efficiency, reduce rework, and elevate delivery quality.
- Support the development and capability building of QA resources through coaching, knowledge transfer, process alignment, and performance guidance to ensure a high-performing and scalable QA team under Business Analytics.
- Participate in leadership and team ceremonies, status discussions, and planning sessions to communicate QA progress, risks, dependencies, and recommendations that help Business Analytics maintain strong quality and predictable delivery outcomes.
Displays (The Knowledge, Skills, and Behaviors indicating how tasks / responsibilities will be performed)
- Strong leadership capability in defining and governing QA strategy, test plans, methodologies, acceptance criteria, and sign-off standards across BA workstreams such as ad hoc requests, reports, dashboards, and ADM/BDM developments.
- Deep grounding in QA concepts, testing disciplines, and control frameworks, with the ability to translate these into scalable BA QA processes, templates, checklists, and team standards.
- Strong knowledge of analytics, data warehousing, and data flow dependencies, enabling effective oversight of validation activities across source, transformation, and output layers and ensuring that BA deliverables are fit for use.
- Strong stakeholder management and cross-functional collaboration skills, able to align effectively with Data Analysts, Embedded Analytics, DAISMs, BA Ops, Governance, requestors, and external partners on scope, timelines, risks, and quality expectations.
- Strong analytical and problem-solving skills in investigating defects, tracing root causes, validating remediation, and driving issue resolution before endorsement to UAT, FRA, or production deployment.
- Strong people leadership skills in mentoring QA resources, driving performance management, building team capability, strengthening knowledge management, and supporting succession and capacity planning for sustained BA QA operations.
Delivers (The specific outputs / tangible results produced by the role; resources responsible for)
- QA strategy, operating plan, and governance standards for Business Analytics, including defined testing approaches, sign-off rules, SLA commitments, quality controls, and prioritization guidelines across ad hoc, reports, dashboards, and ADM/BDM workstreams.
- Standardized QA frameworks, templates, and documentation artifacts such as test plans, QA checklists, test case repositories, evidence packs, traceability records, and sign-off references that support auditability, consistency, and future reuse.
- QA governance reports and metrics dashboards covering testing volume, SLA compliance, defect trends, severity mix, first-pass yield, testing coverage, quality of output, and stakeholder feedback to support performance monitoring and management decision-making.
- Formal QA sign-off, risk assessment, and defect management outputs for BA deliverables, including issue logs, root cause summaries, retest results, and release readiness endorsements prior to UAT, FRA, or production deployment.
- Continuous improvement initiatives for BA QA ways-of-working, including process enhancements, automation opportunities, reusable controls, and updated policies/procedures that improve efficiency, predictability, and scalability of QA support.
- Team capability and operating readiness outputs, including onboarding materials, knowledge assets, coaching plans, resource allocation inputs, and documented best practices that strengthen QA team performance and sustainability.
- Improved BA delivery quality and reduced rework through early detection of defects, stronger QA coverage, and consistent enforcement of testing standards across in-scope requests.
KPIs
- SLA compliance
- Peer review coverage and effectiveness
- Stakeholder feedback on QA support
- Business support efficiency (throughput, QA cycle time)
- Quality of output (defect leakage, rework)
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
