REGINA ROSANN GNANAM

As a senior individual contributor within the Data & Analytics landscape at Shell, I lead end-to-end Quality Assurance for enterprise-grade Azure data products, ensuring high-quality delivery across complex, data-intensive, and business-critical systems. I work extensively across cloud, data engineering, BI, and application layers, owning the full QA lifecycle with strong functional, analytical, and testing leadership.

Key Responsibilities:

• Independently plan, design, and execute comprehensive test strategies, test plans, and detailed test cases for assigned features/modules, ensuring complete alignment with business requirements, workflows, and internal QA standards.
• Own full STLC delivery, including Test Strategy, Test Design, Test Script creation, Execution, Evidence documentation, Defect management, Test Summary Reports, and final QA sign-off.
• Lead QA for Azure-based data products, validating the entire lifecycle from source-system data extraction through ETL/ELT transformations (ADF/Synapse), to visualization in Power BI dashboards used by directors and C-suite executives.
• Conduct functional, integration, regression, UAT, and end-to-end flow testing across deeply interconnected, calculation-heavy enterprise systems.
• Perform complex transformation validations across both Most Confidential (MC) and Non-MC datasets, ensuring strict data accuracy, governance compliance, and business-rule adherence.
• Validate Role Level Security (RLS) in SQL Databases, Power BI, and Power Apps, ensuring robust and secure access models across layers.
• Develop and execute advanced SQL queries for validating data integrity, schema consistency, stored procedures, lineage, and transformation rules.
• Test Azure Data Factory and Synapse pipelines, including triggers, activities, orchestration logic, error paths, and end-to-end pipeline behavior.
• Validate Power BI report quality, including UI/UX, data correctness, DAX formula logic, drill-downs, slicers, relationships, and workspace access configurations.
• Collaborate closely with automation teams to support the manual-to-automation transition, enabling improved coverage and optimized regression cycles.
• Perform deep impact analysis for enhancements, identifying regression scope, risk areas, and high-value test scenarios.
• Track, report, and communicate QA metrics, including coverage, defect trends, risk areas, and release readiness, to stakeholders and leadership.
• Work closely with Product Owners, Developers, BAs, Architects, and DevOps teams for requirement clarification, risk identification, and test readiness alignment.
• Mentor junior QA engineers, provide functional guidance, review test artifacts, and uplift testing capability across the team.
• Experience in performance testing and IT accessibility testing, ensuring system reliability and inclusivity.
• Strong involvement in Agile ceremonies like Sprint Planning, Refinements, Daily Stand-ups, Reviews, and Retrospectives, while also contributing effectively to Waterfall projects when applicable.
• Conduct code reviews for SQL scripts, Power BI DAX, and data transformation logic, proposing optimization improvements for performance and maintainability.
• Ensure strict adherence to QA processes, release checklists, compliance standards, and internal Shell data governance policies.
• Leveraged AI tools with precise prompts to auto-generate test scripts, test cases, and execution steps, drastically reducing manual preparation time and improving test coverage consistency.
• Used AI-driven scenario generation to identify edge-level, negative, and boundary conditions that strengthened functional depth and testing accuracy.
• Enhanced documentation quality by using AI to craft Acceptance Criteria, Test Plans, and supporting QA documentation, with improved clarity, structure, and completeness.
• Integrated AI-assisted workflows into day-to-day QA activities, optimizing productivity, and enabling quicker, smarter delivery of test artifacts.

Tools, Technologies and Skills:

• Cloud/Data: Azure Data Factory, Synapse, ADLS, ADO, SQL Server (SSMS).
• Testing: Functional, Integration, Regression, E2E, RLS Testing, Performance Testing, Accessibility Testing.
• Reporting & BI: Power BI Desktop, Power BI Service, DAX, Power Apps.
• Other tools include Git, Jira, HP-ALM, and DevOps Boards.
• Methodologies: Agile (Scrum), Waterfall, DevOps, CI/CD alignment.
• QA Metrics: Coverage, Defect Density, Severity Analysis, Trend Reporting.

Project: DHL Siebel CRM Implementation

Supported QA delivery for DHL's global Siebel CRM platform a mission-critical system enabling worldwide parcel, shipment, and customer interaction management.

Key Responsibilities:

• Analyzed business requirement specifications, functional documents, and design artifacts to understand CRM workflows, integrations, and end-to-end business processes.
• Designed and authored comprehensive test cases for various CRM modules, and linked them with JIRA to ensure traceability and robust test coverage.
• Performed API testing using SOAP UI, validating request/response structures, web service integrations, and backend CRM interactions.
• Performed cross-browser testing to ensure UI consistency and functional behavior across multiple web environments, improving user experience.
• Conducted functional, integration, system, and regression testing for CRM operations, enhancing overall system reliability.
• Logged, managed, and tracked defects using JIRA, collaborated with cross-functional teams for issue resolution, and re-testing.
• Actively participated in Agile ceremonies, including Sprint Planning, Daily Stand-ups, Backlog Grooming, and Retrospectives.
• Translated complex technical and CRM system behaviors into simple, stakeholder-friendly communication, facilitating better understanding and collaboration.

Tools and skills:

Siebel CRM, SOAP UI, JIRA, and Web Application Testing.