I'm an ISTQB-certified, audio-focused QA/Test Engineer and junior software developer with commercial testing experience and hands-on expertise in audio hardware validation, test automation, full-stack development, and cross-platform systems.

I build structured test projects and software tooling around audio technology, with a particular interest in hardware/software integration, recording workflows, device behaviour, reliability, and reproducible validation across Windows and Linux.

Alongside audio-focused work, I also develop and test general software systems using Python, JavaScript, TypeScript, Java, automated regression testing, APIs, and CI workflows.

🎯 Target roles: Audio QA Engineer • Audio Software Test Engineer • Product Validation Engineer • Audio Software Developer • Test Automation Engineer • QA Engineer

📍 Based in Germany: Open to relocation and opportunities across Europe

🗣️ Languages: English (native) • German and Spanish (fluent)

A cross-platform Python CLI framework for automated audio-device discovery, stream validation, recording, playback, deterministic signal generation, and sample-domain audio analysis across Windows and Linux.

The project is designed around reliable hardware interaction, predictable failure handling, testability, reproducible validation, and hardware-independent automation.

Key features:

• Audio-device discovery and capability inspection
• Input, output, and duplex stream validation
• Finite recording and WAV-based playback
• Deterministic sine-wave and silence generation
• Physical end-to-end loopback validation
• Configurable input/output channel routing
• Captured-signal alignment against known reference signals
• Dominant-frequency measurement
• RMS, peak, and DC-offset analysis
• Silence and clipping detection
• Configuration-driven metric and frequency tolerances
• Structured per-channel validation failures
• Human-readable and JSON CLI reporting
• WAV and JSON evidence retention for passing and failing loopback tests
• WASAPI, WDM-KS, ALSA, JACK, and PulseAudio device/topology investigation
• Deterministic fake backends for hardware-independent testing

Hardware validation & diagnostics:

• Verified physical Scarlett 2i2 loopback through direct ALSA at 48 kHz
• Verified physical JACK loopback with manual runtime graph routing
• Distinguished physical loopback from JACK software/monitor routing
• Used cable A/B/A testing and gain-dependent measurements to verify the analogue signal path
• Documented transient JACK/PortAudio routing limitations and host-API-specific behaviour

Engineering quality:

• Layered backend, service, validation, analysis, and reporting abstractions
• Framework-owned audio buffers, result models, and exception handling
• Deterministic fake-backend coverage of duplex workflows without physical hardware
• Defensive validation of empty, invalid, and non-finite audio inputs
• pytest regression suite with 400 tests and 99% overall coverage
• Strict mypy type checking
• Ruff linting and formatting
• Pre-commit hooks
• GitHub Actions CI

Tech: Python • Numpy • Typer • Pydantic • sounddevice • soundfile • PortAudio • Rich
Quality: pytest • mypy • Ruff • pre-commit • GitHub Actions

A structured cross-platform hardware/software validation project for a Focusrite Scarlett 2i2 across Windows and Linux.

The project applies professional QA methods to real audio hardware, combining requirements analysis, risk-based testing, controlled execution, critical investigation, evidence collection, and final reporting.

Test coverage:

• Device detection and driver/backend behaviour
• Recording and playback workflows
• Signal routing and sample-rate configuration
• Recovery and reconnect behaviour
• Cross-platform compatibility
• Latency and operating-system interactions
• Positive, negative, and repeatable test scenarios

Test environments:

• Windows 11, REAPER, ASIO
• Ubuntu Linux, Ardour, JACK/PipeWire

QA artefacts:

• Test strategy and test plan
• Risk analysis
• Environment documentation
• Traceability matrix
• 26 detailed test cases
• Execution evidence
• Defect documentation
• Final test report

Focus: Audio QA • Hardware Validation • Risk-Based Testing • Cross-Platform Testing • Test Documentation

A full-stack MERN application built with a strong emphasis on maintainability, testability, and automated regression coverage.

Engineering:

• REST API with authentication and authorisation
• Secure per-user data isolation
• Structured Express routing and middleware
• Input validation and error handling
• React frontend with asynchronous API integration
• MongoDB persistence and data modelling

Testing:

• Backend integration testing
• Frontend component testing
• API validation
• Authentication and authorisation testing
• Negative and failure-path testing
• End-to-end browser testing
• 59 automated tests across backend, frontend, and E2E layers

Tech: MongoDB • Express • React • Node.js • JavaScript • TypeScript
Testing: Jest • Supertest • React Testing Library • MSW • Playwright
CI: GitHub Actions

A Java Spring Boot and PostgreSQL REST API for importing chess games and generating player statistics.

Focus: Layered architecture • Relational data modelling • REST API design • Service-layer logic • SQL • Integration testing

A modular Python CLI application with input validation, edge-case handling, and pytest coverage.

An accessible JavaScript web application for calculating media playback durations across different playback speeds.

A collection of practical QA artefacts demonstrating an ISTQB-aligned approach to software quality.

Includes:

• Risk-based test planning
• Equivalence partitioning
• Boundary value analysis
• Negative testing
• Exploratory testing
• Traceability
• Defect reporting
• Regression planning
• Test execution evidence

• Audio Systems: Audio interfaces, signal flow, recording/playback workflows, audio drivers and APIs, sample rates, latency, ASIO, WASAPI, ALSA, JACK, PipeWire, and PulseAudio
• Audio Analysis & DSP: Deterministic signal generation, RMS/peak/DC-offset analysis, silence/clipping detection, FFT and digital-filter fundamentals
• Testing: Manual, exploratory, functional, integration, API, system, regression, and end-to-end testing
• QA Methods: Risk-based testing, test design, defect investigation, traceability, failure-path testing, and test documentation
• Automation: pytest, Playwright, Jest, Supertest, React Testing Library, MSW
• Programming: Python, JavaScript, TypeScript, Java, SQL, C++
• Backend: Node.js, Express, Spring Boot, REST APIs, authentication, and input validation
• Databases: MongoDB, PostgreSQL, SQL
• Tools: Git, GitHub, GitHub Actions, Docker, Postman, Linux, Jira

• ISTQB Certified Tester Foundation Level — August 2025
• Dante Certified Levels 1, 2 and 3 — August 2026
• Bachelor of Music with Honours — University of Huddersfield
• CS50x: Introduction to Computer Science — Harvard Online, 2025
• Algorithms and Data Structures, Part I — Princeton Online, 2024

• Real-Time Operating Systems, e.g. FreeRTOS
• Hardware/software integration
• Test automation and CI-integrated quality workflows
• Python tooling and maintainable software architecture
• DSP (audio signals, FFTs, digital filters, frequency-domain analysis)
• Strengthening C++ for systems and low-level development

• Structured, analytical, and evidence-driven
• Focused on reproducibility, reliability, and maintainability
• Comfortable translating requirements into test scenarios
• Strong technical communicator with professional language-quality experience
• Experienced in documenting expected and actual behaviour clearly
• Curious, pragmatic, and collaborative

📧 Email: joshua-pearson@outlook.com
🔗 LinkedIn: linkedin.com/in/joshua-pearson-qa