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jptrp/README.md

🔍 Dustin Braun

Data Validation Lead | Video Analytics & Platform Integrity

Quality Engineering • Hardware-in-the-Loop Observability • AI Readiness

Python TypeScript Pydantic AWS OpenSearch Playwright GitHub Actions

Data-driven quality engineering: validating what users see against what telemetry claims, powered by explainable heuristics and evidence-backed findings.


🔥 Welcome

I engineer data validation systems, not just test scripts.

My work spans:

  • Data Quality: Correlating ground truth (video) with telemetry claims
  • Observability: Hardware-in-the-loop testing & alignment
  • Automation: Modern testing frameworks with high signal, low noise
  • Integrity: Explainable heuristics over opaque magic
  • Evidence: Screenshot-backed findings with timestamps & confidence

Every repository in this portfolio reflects real engineering standards, not classroom demos.


📦 Portfolio Architecture (Overview)

flowchart TB
    A["Dustin Braun Portfolio<br/>(Data Validation & Quality)"]
    A --> B["Data Validation<br/>Screen-to-Events • Telemetry Integrity • Alignment"]
    A --> C["UI Testing<br/>WebdriverIO • Playwright • Cypress"]
    A --> D["API Testing<br/>Postman • Newman • Schema Validation"]
    A --> E["Performance & Security<br/>k6 • OWASP ZAP • CI Integration"]

    click B "https://github.com/jptrp/signal-noise-screen2events" "Data Validation"
    click C "https://github.com/jptrp/saucedemo-wdio-automation" "UI Automation (WDIO)"
    click D "https://github.com/jptrp/saucedemo-api-testing-postman" "API Testing (Postman)"
    click E "https://github.com/jptrp/k6-zap-perfsec-automation" "Performance (k6) + Security"
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🧩 Portfolio Projects

📊 Project Matrix

# Project Tech Stack Key Capabilities Links
Signal & Noise (Screen-to-Events)
Hardware-in-the-loop observability
Python Pydantic AWS_S3 OpenSearch • Video-derived state timeline
• Telemetry correlation engine
• Multi-device support (Roku/Apple TV)
• Time alignment & drift estimation
• Evidence-backed findings
• S3/Athena/OpenSearch adapters
Repo
ERP Test Automation
Enterprise system showcase
Cypress Node AWS Azure • MVP ERP (4 modules)
• 190 TestRail test cases
• Feature flags (A/B testing)
• Dual CI/CD (AWS + Azure)
• 90% automation
Repo
Video Data Quality Lab
ML/AI testing framework
Python OpenCV ML • Computer vision testing
• ML model validation
• Video quality metrics
• Automated analysis
• Research-grade
Repo
4 WebdriverIO UI Automation
Production framework
WDIO TS Allure • POM Architecture
• 3 Test Suites (Smoke/Regression/E2E)
• CI/CD + Allure Reports
• ESLint/Prettier/Husky
RepoCIReports
5 API Testing
Contract validation
Postman Newman • 11-endpoint suite
• JSON schema validation
• Negative testing
• CI-ready
Repo
6 Playwright UI
Modern automation
Playwright TS • Cross-browser testing
• Trace viewer
• Deterministic selectors
• Fast execution
Repo
7 Cypress UI
Developer experience
Cypress TS • Fast dev cycles
• Custom commands
• Strong debugging
• Time-travel debugging
Repo
8 Performance + Security
Non-functional testing
k6 ZAP • Load testing with thresholds
• ZAP baseline scanning
• Combined perf + security
• CI integration
Repo

🎯 What This Demonstrates

  • Data Validation & Observability → Correlating ground truth (video) with telemetry claims, aligning timelines, detecting anomalies
  • Computer Vision & Video Analysis → State detection, motion analysis, OCR-based signals, explainable heuristics
  • Telemetry Integrity → Normalized adapters for S3, Athena, OpenSearch; session/device identity resolution
  • UI Automation Mastery → 3 modern frameworks (WDIO, Playwright, Cypress) with POM architecture
  • API Testing Expertise → Schema validation, contract testing, normalization pipelines
  • Non-Functional Testing → Performance + Security (k6, OWASP ZAP) integrated with CI/CD
  • Production Standards → Type-safe design (Pydantic, TypeScript), comprehensive docs, explainable heuristics

🧠 Engineering Philosophy

Data Validation & Automation are engineering disciplines.

I operate by these principles:

  • Screen is Truth → Video is ground truth, telemetry is claims to validate
  • Explainability > Opaque Magic → Deterministic heuristics over ML black boxes
  • Evidence-Backed Findings → Mismatches backed by screenshots, timestamps, confidence scores
  • Stability > Speed
  • Clarity > Cleverness
  • Architecture > Accumulation
  • Real Coverage > Illusion of Tests

These tools aren't written to simulate production or automate clicks —
they're written to validate claims, detect anomalies, and improve decisions at scale.


🛠️ Technical Skills

Languages: Python, TypeScript, JavaScript
Data Validation: Pydantic, Video Processing, Computer Vision, State Machines, Correlation Engines
Telemetry Adapters: S3, AWS Athena, OpenSearch, JSONL normalization
UI Automation: WDIO, Playwright, Cypress, Selenium
API Testing: Postman, Newman, Playwright API, schema validation
Performance & Security: k6, OWASP ZAP
CI/CD: GitHub Actions, Docker
Architecture: POM, Adapters, Fixtures, Utilities, Data Strategies, Evidence Export


📫 Contact

Dustin Braun
Data Validation Lead | Video Analytics & Platform Integrity
📍 Castle Rock, CO
🔍 Focus: Telemetry Integrity, Hardware-in-the-Loop Observability, AI Readiness
📧 jptrp@icloud.com
🔗 https://www.linkedin.com/in/dustinbrauntesting/
🐙 https://github.com/jptrp


This portfolio represents how I think about quality, data integrity, reliability, and engineering — from validation systems to test automation.

⭐ Star this repo if you'd like
🔄 Updated: January 2026

@jptrp's activity is private