Portfolio

Selected projects demonstrating measurable impact across different domains and engagement types.

Reports & Billing Department

US-Based Hospitality Company

90% Regression cycle reduction
— Defect escape rate (TBD)
— Cost savings (TBD)

Situation: A US-based hospitality client relied on complex client, facility, and transactional data stored in databases. They initiated a project to build a new centralized "Reports & Billing" department as a standalone product. The challenge was ensuring accuracy of financial calculations, data aggregation across multiple sources, and timely delivery of critical client invoices and P&L statements.

Task: As QA Team Lead, I architected a comprehensive quality strategy to validate the entire data pipeline—from source systems to final reports and bills—and built a future-proof test automation framework to ensure regression stability, moving the team away from purely manual verification.

Action: I led a shift-left approach collaborating with Business Analysts during requirements engineering to create testable acceptance criteria. I designed a hybrid automation framework:

  • API/Data Layer: Used ReadyAPI with data-driven tests validating business logic and calculations at the service layer, including complex SQL queries for data transformation verification.
  • UI Layer: Built Selenium WebDriver framework in Python for end-to-end validation of report generation, user interactions, and billing statement presentation.
  • Team Leadership: Mentored QA team on automation best practices, transitioning them from manual testers to automation-capable SDETs.

Result: The "Reports & Billing" product launched successfully as a dedicated, revenue-generating service. Our automation strategy reduced the regression cycle for critical billing functions by over 90% (from days to hours), establishing a scalable foundation for future enhancements.

Interested? Let's Connect

Betting Engine Framework

Sports Betting Company

70% Faster test scenario creation
— Scenario coverage (TBD)
— Critical defects caught (TBD)

Situation: A sports betting company's core betting engine was highly complex with numerous interdependent rules (odds calculation, bet types, stake limits, settlement logic). The business required maximum test coverage to ensure mathematical accuracy and regulatory compliance. The existing approach was ad-hoc with manual test case sprawl and non-scalable scripted automation, leaving significant risk of undiscovered edge-case defects.

Task: As Senior QA, I had two primary objectives: mentor and upskill junior QA specialists in advanced test design techniques to systematically deconstruct the engine's logic, and design a robust, data-driven automation framework that could efficiently cover vast matrices of possible betting scenarios.

Action: I conducted dedicated workshops on requirements analysis and test case design, teaching the team to identify happy paths, systematically derive boundary value analysis and negative test scenarios using decision tables and state transition diagrams. I architected a parameterized, data-driven automation framework in C# using TestComplete:

  • Core Framework: Built modular framework separating test logic from test data (BetType, Stake, Odds, ExpectedResult).
  • Data-Driven Design: Created external data sources enabling a single test script to execute hundreds of unique test permutations.
  • CI Integration: Integrated into CI pipeline for nightly regression runs, empowering team to extend coverage autonomously.

Result: Created the company's most comprehensive regression pack covering most scenario combinations. The parameterized approach reduced time to add new test scenarios by over 70%. The framework caught several critical boundary-defects related to odds rounding and settlement timing before release. Junior specialists evolved into competent test designers, and the framework became the foundation for all future betting product testing, delivering long-term ROI.

Interested? Let's Connect

FIX Protocol Validation Tool

US-Based Hedge Fund - Algorithmic Trading

10 min Review time (was hours)
0 Config-based defects post-launch
— Risk mitigation value (TBD)

Situation: Platform & Connectivity teams were integrating new algorithmic trading clients, each providing custom "algo-packs" extending the standard FIX (Financial Information eXchange) protocol with proprietary tags and logic. Manual validation was error-prone and posed significant financial risk; a single misconfigured or duplicate tag could lead to failed trades, monetary loss, or broken connectivity.

Task: As Senior QA embedded in the connectivity team, I needed to guarantee integrity and uniqueness of every client's FIX protocol implementation, moving validation from reactive manual checklists to proactive, automated safety gates integrated into the client onboarding lifecycle.

Action: I immersed myself in the FIX protocol domain through hands-on participation in 3 new trader onboardings, identifying precise pain points where engineers manually compared algo-packs with no systematic conflict detection. I designed and built a custom ETL parser and validation engine in C#:

  • Core Functionality: Ingested and parsed client-provided algo-pack configurations, performed deep analysis to enforce tag uniqueness, and validated structure against internal schema definitions.
  • Integration: Plugged validation results directly into TestRail, creating standardized, auditable reports for each client pack.
  • Process Institutionalization: Redefined onboarding SOP to make ETL validator execution and TestRail report review mandatory "Step Zero" before integration testing.

Result: Eliminated configuration-based connectivity defects in the onboarding process. Automated validation cut initial technical review time for algo-packs from several hours to under 10 minutes. Introduced critical preventive safety layer, mitigating risk of costly trading errors. Generated TestRail cases became reusable knowledge base, ensuring consistent rigor for every new trader onboarding. This established QA as a key enabler for safe, scalable business growth in high-stakes trading.

Interested? Let's Connect