QA Engineer

👋 A bit of background on Rotageek

Rotageek helps businesses optimise staff scheduling through data-driven technology. By combining machine learning and advanced algorithms, we help organisations forecast demand, improve workforce management and give employees greater control over their schedules.

Our solutions drive operational efficiency, improve customer experiences and help reduce staff turnover across the retail and healthcare sectors. Rotageek is now part of the ELMO Software group, strengthening our ability to deliver industry-leading workforce management solutions as part of a broader HR technology ecosystem.

Confidence can sometimes hold us back from applying for a job. But we’ll let you in on a secret: there’s no such thing as a “perfect” candidate.

Rotageek is a place where everyone can grow. So, however you identify and whatever background you bring with you, please apply if this is a role that would make you excited to come into work every day.

💛 Our values: what we live by

🫶 Start With People: You champion the customer experience, create psychological safety and help the whole team deliver with confidence.

🤝 Own It, Together: You take responsibility for quality outcomes, collaborate across disciplines and help turn incidents into learning.

🙌 Clear Is Kind: You make defects, risks, coverage and quality decisions clear, actionable and respectful.

💡 Why this role is so important

Quality is central to the trust our customers place in Rotageek. As a QA Engineer, you’ll help make sure our product works for the people who rely on it every day, from the journeys they take through the product to the data and insights they use to make decisions.

You’ll work closely with Engineering, Product and Data colleagues from the beginning of the delivery process. You’ll help the team identify risk early, design effective coverage and make confident release decisions.

This is not a role where QA waits at the end of the process. You’ll combine automation, exploratory testing and customer thinking to find the risks that matter most and turn learning into better ways of working.

You’ll also have the opportunity to use AI-assisted testing tools to broaden ideas, generate scenarios and accelerate automation, while applying the human judgement needed to validate the results.

🛠️ What you’ll be doing

• Collaborate on requirements and designs early, helping the team make features clear, testable and valuable for customers.

• Plan testing for features and epics, identifying risk, dependencies, coverage needs and realistic timelines.

• Execute exploratory, functional, regression and smoke testing across important user journeys and real-world scenarios.

• Apply risk-based testing, focusing depth where customer impact, data sensitivity or failure consequences are highest.

• Design and maintain reliable automated tests at the right level, integrating them into CI/CD for fast feedback.

• Manage test data and environments so testing is repeatable, representative and appropriately isolated.

• Investigate and manage defects through to resolution, with clear reproduction steps, appropriate prioritisation and thoughtful root-cause analysis.

• Validate performance, reliability, usability and accessibility at feature level.

• Work with Data Engineering colleagues to validate data integrity, completeness, consistency, transformations and customer-facing analytics outputs.

• Use test results, defect trends, logs and production signals to communicate quality, risk and release readiness.

• Contribute to incident learning, test reviews, retrospectives and improvements to our tools, coverage and processes.

✅ What you’ll bring

• Professional experience in QA or software testing within an agile product team.

• Practical experience with exploratory, functional, regression and automated testing.

• Experience creating and maintaining automated tests and integrating them into CI/CD workflows.

• Strong defect investigation, reproduction, triage and root-cause analysis skills.

• An understanding of test data, test environments, quality metrics and risk-based coverage.

• Awareness of performance, usability, accessibility, security and reliability considerations.

• Clear communication and confidence working with Engineering, Product, QA and Data stakeholders.

• A customer mindset: you care about whether a feature works for the person using it, not just whether the implementation matches the specification.

• The judgement to use AI and automation to increase coverage and speed while retaining human responsibility for quality.

🌱 Nice to have, but not essential

• Experience testing data-heavy products, analytics features, reporting workflows or business intelligence experiences.

• Strong SQL and experience validating datasets, transformations, aggregates, completeness, consistency or lineage.

• Experience testing data pipelines, ingestion workflows, event-driven integrations or cloud data platforms.

• Familiarity with data contracts, semantic layers, warehouse models or tools such as Snowflake, BigQuery, Redshift, Databricks, dbt or ThoughtSpot.

• Experience testing multi-tenant systems, row-level security, permissions, PII masking or GDPR-sensitive workflows.

• Experience helping Engineering teams design for testability and observability.

You don’t need experience with every tool listed above. We’re more interested in your testing judgement, curiosity and ability to learn.

🤝 How you’ll work

• You engage early, rather than waiting for a finished build.

• You automate where it gives reliable value and use exploratory testing where human judgement adds something unique.

• You think like a customer and focus on the journeys and outcomes that matter.

• You are pragmatic about scope: thorough on high-risk areas without creating low-value over-testing.

• You communicate clearly about coverage, uncertainty, defects and release readiness.

• You share knowledge, improve the test suite and raise blockers early so the team can keep moving.

📈 The impact you’ll make

• The team gets fast, trustworthy feedback without treating QA as a late-stage gate.

• High-risk customer journeys have the right balance of automated and exploratory coverage.

• Releases are made with a clear view of quality, risk and customer impact.

• Data quality issues are found before they become misleading product or analytics experiences.

• We learn from defects, incidents and customer feedback, improving the way we build and test.

• Engineering, Product and Data colleagues see you as a partner who improves delivery.

🔧 The tools and ways of working

• Test automation for web, API and service-level scenarios in a .NET product environment.

• CI/CD-integrated testing, Git and test reporting or quality dashboards.

• SQL and structured test data, with an interest in validating data flows and transformations.

• Logs, metrics and observability tools for diagnosis and production feedback loops.

• Agile planning, quality discussions, defect management and collaborative release decisions.

• AI-assisted testing tools used with human review, validation and responsible data handling.

🎁 Why you’ll love it here

• Competitive salary, dependent on experience.

• Flexible, hybrid working, with collaboration across the team and time to focus when you need it.

• 25 days’ holiday, plus one extra day after three years, and your birthday off.

• UK bank holidays, plus Christmas Eve and New Year’s Eve afternoons off.

• Private medical insurance with enhanced mental health, dental and optical coverage via AXA.

• Employee Assistance Programme — support when you need it.

• Life insurance at 2x salary and matched pension contributions of 5%.

• Two volunteer days per year — give back to causes that matter to you.

• Access to Mintago for financial wellbeing, discounts and expert advice.

• Retail discount scheme — perks and savings just for being part of our team.

🚀 The hiring process: let’s make it personal!

Screening call: A virtual chat with one of our team to learn more about your experience, what excites you about the role and how you align with our people-first culture.

Competency interview: You’ll meet the hiring manager and talk through your approach to quality, automation, risk-based testing, defect investigation and working with Engineering, Product and Data.

Final stage interview: You’ll meet members of the wider team and explore how you would help us improve coverage, release confidence and customer outcomes.