Quality Engineer

Fintech, Automotive & Trading Platforms

I catch bugs before they become problems.

Experienced

Test Automation Engineer

QA/QE/SDET | 10+ years | Front & Back End | Java | Ford, Aviva | Now at Create Future (FanDuel, Wood Mackenzie, Evoke) | London

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A Little About Me

I Love To Travel

Studying in the U.S. broadened my worldview and sparked a love for diversity and exploration. I’ve since lived in Michigan, Warsaw, and London—and traveled to 60+ countries.

Full-Stack Testing

My experience includes frontend testing of user interfaces and backend testing of services, data handling, and application logic.

Front End

Back End

Git Repositories

Mainly basic projects and practice work I can revisit or use as quick references. It’s a simple archive of things I’ve built and learned from.

Take A Look

Digital Shelf

It’s more of a personal collection—random things I come across, resources worth remembering, and thoughts I might want to come back to later. Just a place to keep track of it all.

Docker + Cypress

Precondition Install Docker Desktop: https://www.docker.com/products/docker-desktop/ Example setup: Core Idea Image = instructions (what to install + what to run) Container = running version of image Flow: Cypress Docker images: https://github.com/cypress-io/cypress-docker-images Dockerfile .dockerignore package.json docker-compose.yml Commands (minimal reference) Build image Run container Using docker-compose (recommended) When to Rebuild Rebuild if you change: Dockerfile pa

Cypress Reports

When Cypress tests run in headless mode (npx cypress run) , the default reporting is quite limited. You typically get: terminal output screenshots for failures videos (if enabled) While useful, this makes debugging difficult in larger test suites or CI pipelines because there is no clear HTML dashboard summarizing test results. To solve this, Cypress supports custom reporters . Official documentation: https://docs.cypress.io/app/tooling/reporters Why Use Custom Reporters Cus

Data-Driven Testing in Cypress

Data-driven testing means running the same test multiple times with different input data . Instead of writing several almost identical tests, a single test can iterate through a dataset and validate different scenarios. This approach is especially useful for: form validation boundary testing error message verification repetitive input testing It reduces duplicated code and makes tests easier to maintain. Example Scenario – Username Validation In this example the Conduit appli

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