Quality Assurance Engineer

Overview
A new-generation technology consultancy operating across the UK and Europe is hiring a senior Quality Assurance Engineer on a fully remote B2B contract. The role is based anywhere in Poland, with an optional office in Warsaw for those who prefer it. Occasional client visits to the UK are expected once or twice a year, always arranged well in advance. The rate is EUR 350-400 per day net, reflecting a senior-level engagement.

This role exists because the team needs someone to own quality end-to-end across data-heavy, cloud-native projects, not just execute test scripts. You will be the quality conscience of the project: designing and implementing automation frameworks, validating ETL pipelines, setting up CI/CD-integrated test pipelines, and communicating data behaviour clearly to both technical and non-technical stakeholders. The consultancy works across modern tech stacks in agile environments, which means the right person will flex across different project contexts without losing rigour. Beyond project delivery, there is a genuine expectation that you will contribute to QA practice across the whole business, helping to raise standards, share knowledge, and build automation approaches that benefit every team.

Key Responsibilities

• Design and implement Python-based test automation frameworks based on BDD (Behave)
• Test ETL pipelines, validate data quality, and ensure data meets defined requirements
• Script and maintain automated tests within a continuous build environment
• Set up and maintain automated test pipelines, working alongside cloud engineers where needed
• Integrate tests into CI/CD pipelines using tools such as AWS Pipelines or GitHub Actions
• Communicate data requirements and testing outcomes clearly to technical and non-technical stakeholders
• Clarify ambiguous requirements proactively, rather than waiting for clarity to arrive
• Use AI tools such as Claude to improve test automation, test design, and overall delivery
• Adopt and adapt AI tools and solutions into QA workflows and automation processes
• Contribute to QA standards and automation practices across the consultancy, beyond individual project work
• Carry out manual testing where project constraints or timelines require it

Requirements
Must-haves

• 2+ years of Python test automation, hands-on and recent
• ETL pipeline testing and data validation experience
• Strong PyTest and SQL skills
• CI/CD knowledge, preferably AWS or GCP
• Understanding of cloud architecture principles
• Clear, confident communication with non-technical stakeholders
• Proactive approach to identifying and resolving quality risks
• Comfortable working remotely across cross-functional teams
• Eligible to work in Poland under a B2B contract
• Available to start immediately, within 2-4 weeks, or within 30 days

Nice-to-haves

• Behave BDD experience
• Hands-on AI integration in QA or data engineering workflows
• Experience contributing to team-wide standards or practice development

What Success Looks Like

• Automated test frameworks delivered and trusted by the team within the project timeline
• Data quality risks identified and addressed before they reach production
• Stakeholders, technical and non-technical, have a clear shared understanding of data behaviour and test coverage
• Positive feedback from teammates, reflecting genuine collaboration and knowledge-sharing
• A tangible contribution to QA practice across the consultancy, such as shared automation standards or AI-driven solutions that other teams can use

Team and Culture

• Agile, scrum-based delivery across varied projects and tech stacks
• Automation-first and AI-first mindset is the norm, not the aspiration
• Fully remote team, with the communication discipline and proactiveness that requires
• A consultancy that expects its people to look beyond their current project and help raise the bar for everyone

Challenges

• Requirements are often unclear at the outset, and the right person defines and documents them rather than waiting for someone else to
• Remote, cross-functional teams mean communication has to be deliberate and consistent, especially when bridging technical and non-technical perspectives
• Knowledge silos are a real feature of consultancy work, and bringing them together takes patience and persistence
• Projects can be short, so frameworks and standards need to be established quickly and built to be reusable, not tailored to a single engagement