QA Automation Engineer
Kratos Growth's client is hiring QA Automation Engineers (Remote)
Join a rapidly growing AI consumer intelligence platform delivering insights for global brands
Hiring Company Background
Led by industry veterans from Unilever and Coca-Cola, our platform synthesizes massive-scale data (billions of Google searches, social conversations, product reviews, and videos) to deliver actionable consumer insights for Fortune 500 clients in days instead of months.
Our clients include global leaders in beverages, personal care, and consumer packaged goods.
With a newly appointed CTO building our engineering team, this is your opportunity to shape engineering standards, define AI architecture, and establish product strategy at a high-growth company, while working remotely from anywhere in the world as we scale in 2026 and beyond.
This is your chance to shape how production AI is built at a high-growth company. Your impact will be immediate and visible. No legacy code politics, no entrenched hierarchies, no technical debt that you’re powerless to change.
Your Mission
We are seeking a skilled QA Automation Engineer to join our data engineering team. You will be responsible for designing, developing, and maintaining automated testing frameworks that ensure the quality and reliability of our data pipelines, dashboards, and web applications.
Our platform processes data from multiple sources, through Azure Databricks pipelines, and presents insights via dashboards embedded in ASP.NET and React web applications. You will play a critical role in validating data integrity across this entire flow and automating operational processes.
This is a hands-on technical role requiring strong programming skills, database expertise, and a passion for building robust automation systems.
Key Responsibilities
Test Automation Development
• Design, develop, and maintain automated test frameworks using Python and pytest
• Create end-to-end test suites for validating data pipelines from ingestion through visualization
• Implement browser automation using Playwright for testing Power BI and React dashboards, ASP.NET, and React web applications
• Build API test suites to validate data provider integrations and internal services
• Develop data validation tests comparing Web and Azure Databricks outputs against Azure Databricks and SQL Server production databases
Dashboard & Reporting Validation
• Automate verification of Power BI/React dashboard KPIs against source data
• Implement visual regression testing for dashboard layouts and components
• Validate user-facing metrics in ASP.NET and React applications match database values
• Test dashboard performance and load times under various conditions
Process Automation
• Automate repetitive operational tasks related to data pipeline management
• Build scheduled jobs for recurring QA checks
• Create self-healing automation that handles common failure scenarios
• Develop monitoring scripts that proactively identify pipeline issues
CI/CD & Infrastructure
• Integrate automated tests into CI/CD pipelines
• Configure test environments and manage test data
• Implement parallel test execution for faster feedback cycles
• Maintain test reporting dashboards using Allure or similar tools
Collaboration & Documentation
• Work closely with data engineers to understand pipeline logic and identify test scenarios
• Collaborate with front-end developers on dashboard testing strategies
• Create and maintain technical documentation for test frameworks and processes
• Participate in code reviews and contribute to engineering best practices
• Report defects through Jira with detailed reproduction steps and evidence
Required Qualifications
Technical Skills
Programming: 6+ years of Python development experience; clean, maintainable code
Test Automation: 4+ years building automated test frameworks; pytest expertise
SQL: SQL skills; experience with SQL Server and/or cloud data warehouses
Browser Automation: Expertise with Playwright
API Testing: Proficiency in REST API testing and validation
Version Control: Git proficiency; branching strategies, pull requests
CI/CD: Experience integrating tests into CI/CD pipelines
Database & Data Skills
• Understanding of data warehousing concepts and ETL/ELT processes
• Experience validating data transformations and business logic
• Familiarity with data quality dimensions (accuracy, completeness, timeliness, consistency)
Web Technologies
• Understanding of web application architecture (front-end/back-end)
• Experience testing Single Page Applications (React)
• Knowledge of HTML/CSS/JavaScript for element identification and validation
• Familiarity with headless browser developer tools for debugging
Soft Skills
• Strong analytical and problem-solving abilities
• Attention to detail and commitment to quality
• Excellent written and verbal communication
• Ability to work independently and prioritize tasks
• Proactive mindset; identifies issues before they reach production
Preferred Qualifications
Highly Desirable
• Experience with Azure Databricks or Apache Spark
• Familiarity with Power BI or other BI tools
• Knowledge of Azure cloud services (Functions, Data Factory, Key Vault, DevOps)
• Experience with ASP.NET or .NET ecosystem
• Background in data engineering or analytics
Nice to Have
• Experience with performance testing (Locust, k6, or similar)
• Knowledge of containerization (Docker) for test environments
• Familiarity with infrastructure-as-code (Terraform, ARM templates)
• Experience with test management tools (Xray, Zephyr, TestRail)
• Understanding of machine learning pipelines and model validation
• ISTQB or similar QA certification
Technical Environment
You will work with the following technology stack:
Processing: Azure Databricks (PySpark), Custom ML Models
Storage: SQL Server, Azure Blob Storage
Visualization: Power BI (embedded dashboards), Apache Superset
Web Applications: ASP.NET (C#), React (JavaScript/TypeScript)
Cloud Platform: Microsoft Azure
Automation Stack You Will Build & Maintain:
Language: Python 3.11+
Test Framework: pytest
Browser Automation: Playwright
API Testing: httpx / requests
Database Clients: pyodbc, databricks-sql-connector
Data Manipulation: pandas
Configuration: YAML + Pydantic
Scheduling: Azure Functions / APScheduler
Reporting: Allure, pytest-html
Success Metrics
You will be measured on:
Test Coverage: Automated tests cover critical data paths and dashboard KPIs
Defect Detection: Bugs caught in automation before reaching production
Pipeline Reliability: Reduction in data quality incidents
Automation ROI: Manual testing hours saved through automation
Test Stability: Low flaky test rate (<5%); high first-pass success
Execution Speed: Test suite runs complete within CI time budgets
Growth Opportunities
This role offers paths to:
• Senior QA Automation Engineer – Lead automation architecture decisions
• QA Lead – Manage QA team and strategy
• SDET / Software Engineer in Test – Deeper integration with development
• Data Quality Engineer – Specialize in data pipeline quality
• DevOps/Platform Engineer – Focus on CI/CD and infrastructure
What We Offer
• Competitive salary and benefits package
• Flexible remote and hybrid working arrangements
• Professional development budget for training and certifications
• Modern tech stack with latest tools and frameworks
• Collaborative engineering culture with knowledge sharing
• Opportunity to shape QA practices from the ground up
• Work with interesting data from multiple industries
QA Automation Engineer
QA Automation Engineer