QA Analyst

At the World Bank, a member of the World Bank Group (WBG), you’ll join a diverse, global community working across cultures, disciplines, and borders to address the world’s most pressing development challenges. With 1.2 billion young people reaching working age in the decade ahead, the challenge of job creation has never been greater. Through partnerships across 145 countries and more than 182 offices worldwide, we work with governments, private sector, development partners and other stakeholders to invest in people, strengthen markets, and deliver scalable, data-driven solutions that generate more and better jobs and improve lives.

For more information, visit https://www.worldbank.org/en/who-we-are/ibrd ITS Vice Presidency Context The Information and Technology Solutions (ITS) Vice Presidential Unit (VPU) enables the World Bank Group to achieve its mission of ending extreme poverty and boost shared prosperity on a livable planet by delivering transformative information and technologies to its staff working in over 150+ locations. For more information on ITS, see this video: https://www.youtube.com/watch?reload=9 v=VTFGffa1Y7w Background Context The World Bank Group (WBG) is investing in a modernized enterprise data ecosystem - consolidating structured and unstructured data sources, establishing a governed semantic layer, and delivering certified data products through governed APIs, dashboards, and a unified Data Marketplace. As the volume and criticality of enterprise data products grows, so does the need for a disciplined, end-to-end quality assurance function that ensures every product is functionally sound, data-accurate, and release-ready before it reaches enterprise consumers.

The Product Assurance Operations team is responsible for Quality Assurance, Security Accreditation, and Post-Production Support across all enterprise data products and services. The QA Analyst will be responsible for end to end QA function- from test strategy and planning through execution, defect management, release gating, and continuous quality improvement. Purpose of the Role The QA analyst is responsible for establishing and running a structured, rigorous quality assurance practice for enterprise data products and services.

This includes designing the QA framework, leading test planning and execution, managing defects through to resolution, enforcing release gates, and driving continuous improvement in quality outcomes. The role requires both strategic thinking - building the QA practice from a governance and standards perspective - and hands-on execution in a fast-moving delivery environment. The QA analyst works closely with the Product Owner, Program Coordinator, UX Designer, Development Team, and Security Team to ensure quality is embedded at every stage of the delivery lifecycle, not applied as an afterthought at the point of release.

Key Responsibilities 1. QA Strategy Framework Design

• Design, document, and maintain the QA framework for enterprise data products, defining quality dimensions, testing types, acceptance thresholds, entry and exit criteria, and the overall approach to quality assurance across the delivery lifecycle.
• Develop QA playbooks covering functional testing, data reconciliation, regression testing, performance testing, API testing, and User Acceptance Testing (UAT), tailored to the specific characteristics of enterprise data products.
• Define and enforce the QA acceptance checklist and definition of done for all data product releases, ensuring quality standards are agreed upfront and applied consistently.
• Champion a shift-left quality philosophy, embedding testing activities early in the delivery cycle to reduce the cost and disruption of late-stage defect discovery. 2. Test Planning Preparation
• Prepare a detailed test plan for each enterprise data product release, covering test scope, objectives, test types, resource allocation, environment requirements, schedule, and risk assumptions.
• Develop and maintain a comprehensive test case repository for all enterprise data products, aligned to functional requirements, data quality rules, API contracts, KPI definitions, and business rules, updated with each release cycle.
• Identify and document test data requirements for each test cycle, coordinating with the development team to ensure appropriate test environments and data sets are available before testing begins.
• Assess and communicate testing risks to the Product Owner ahead of each release, recommending mitigations where coverage gaps or resource constraints exist. 3.

Test Execution Defect Management

• Lead and execute end-to-end testing across all applicable test types for each enterprise data product release: functional, regression, data reconciliation, performance, API, accessibility, and UAT.
• Conduct source-to-target data reconciliation testing to validate that certified gold data assets trace accurately from source through transformation to consumption, with no data loss, distortion, or misalignment.
• Log, classify, and manage all defects identified during testing in the agreed tracking system (Jira or Azure DevOps), ensuring each defect is clearly described, severity-rated, assigned to the responsible owner, and tracked to verified closure.
• Conduct defect triage sessions with the development team and Product Owner, prioritizing resolution by business impact and release risk.
• Enforce the release gate: no enterprise data product proceeds to production without formal QA sign-off confirming all critical and high-severity defects are resolved and agreed exit criteria are met. 4. Automated Regression Testing
• Design, build, and maintain an automated regression test suite covering all certified KPIs, canonical data definitions, API contracts, and critical business rules, ensuring automated tests run on every pipeline update or schema change.
• Integrate automated tests into the CI/CD pipeline to enforce continuous quality gates throughout the development cycle, not only at release time.
• Monitor automated test results, investigate failures promptly, and escalate emerging quality risks to the Product Owner and development team before they impact release timelines.
• Continuously improve the coverage, reliability, and efficiency of the automated test suite as the enterprise data product portfolio grows. 5. Data Quality Assurance
• Execute data quality checks at each stage of the delivery lifecycle, from initial data profiling through integration testing and production validation.
• Identify and escalate data quality risks that could affect the integrity of enterprise reporting, KPIs, or analytical outputs before they reach consumers. 6.

User Acceptance Testing (UAT) Coordination

• Plan and coordinate UAT for each enterprise data product release, managing scheduling, test environment readiness, participant communication, and feedback collection.
• Work with business stakeholders to define UAT test scenarios, acceptance criteria, and success thresholds before testing begins.
• Compile, triage, and document UAT findings, distinguishing between defects requiring resolution, change requests for the enhancement backlog, and observations for future consideration.
• Obtain and document formal UAT sign-off from business owners as a mandatory release gate. 7. Security Compliance Testing Support
• Coordinate with the Security Team to ensure security-related test requirements - access control validation, data masking verification, audit log testing, and API authentication checks - are incorporated into the QA test plan for each release.
• Support the security accreditation process by providing QA evidence and test results required for the security team's review.
• Ensure that re-accreditation triggers - schema changes, access scope changes, infrastructure updates - are identified during QA activities and communicated to the Security Team promptly. 8. Reporting Stakeholder Communication
• Prepare and distribute QA status reports for each sprint and release, summarizing test execution progress, pass/fail rates, defect status by severity, release readiness assessment, and any risks requiring Product Owner decisions.
• Maintain the QA tracker as a live, accurate record of all test activities, defects, and sign-off statuses, accessible to all relevant stakeholders at all times.
• Present QA findings and release readiness assessments to the Product Owner and program leadership in a clear, business-relevant manner - not just technical metrics.
• Contribute QA data and insights to the broader program health dashboard and operational reporting cycle managed by the Program Coordinator. 9.

Post-Release Quality Monitoring Continuous Improvement

• Monitor post-release quality signals - production incidents, data quality complaints, consumer feedback - and assess whether they indicate gaps in the QA process that need to be addressed.
• Participate in post-incident reviews for major production incidents, contributing QA perspective on root cause and recommending process improvements to prevent recurrence.
• Maintain and continuously improve the regression test suite, test case repository, and QA playbooks, incorporating lessons learned from each release cycle.
• Track and report quality improvement trends over time - defect escape rate, test coverage, automated test pass rate - demonstrating the value and maturity of the QA function to program leadership.