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RepRisk AG logo

Quality Engineer

RepRisk AG
Posted Jun 29, 2026, 3:28 PM UTC
🇩🇪Germany🏢Hybrid📁Engineering & Development
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About Us RepRisk is the world’s most respected Data as a Service (DaaS) company for reputational risks and responsible business conduct. Our mission is to provide transparency on business conduct risks to drive positive change. Combining advanced AI with deep human expertise, and a proven methodology at the core, RepRisk’s solutions bring performance and peace of mind, enabling clients to know more, be sure, and act faster. With our values of intellectual honesty and humility, operational excellence, and openness and respect, our diverse teams of talented experts are pioneering solutions that enable clients to make better informed decisions. Headquartered in Zurich, and with offices in Toronto, New York, London, Berlin, Manila, and Tokyo, we stay close to clients and bring an independent lens to the industry. United by our shared belief in the power of data, our 400 people are proud to be setting the global standard for business conduct data and driving positive and meaningful change through transparency. We Offer We offer a diverse, multicultural, and missiondriven workplace where your impact truly matters. You’ll join a collaborative team that values openness, respect, and work–life balance. What you can expect: Flexible working hours and a hybrid model (with home office days). Up to 4 weeks per year working abroad, subject to policy and approvals. Paid training and volunteering days, plus charity donation matching. Health & fitness subsidy to support your wellbeing. Frequent team and social events that bring our global community together. A welcoming office environment with complimentary coffee, refreshments, fresh fruit, and healthy snacks. A company that embraces diversity and values different perspectives. About You You are an engineer who thinks about quality as a system property, not a testing activity. You are interested in how systems fail, how issues propagate across components, and how to design mechanisms that detect and prevent them early. You have contributed to automation frameworks, quality tooling, or quality engineering practices in complex systems. You enjoy working across teams and are interested in improving how quality is implemented and measured at scale. If that’s YOU – then this is the perfect role for you! Your Responsibilities As our new Quality Engineer, you will help build and improve the frameworks, tooling and automation that allow teams to continuously validate, observe, and improve their systems. You will be part of our global Technology division and report to the Global Head of Quality Engineering, based in Berlin, Germany. In this role you will: Build and integrate automated checks across data pipelines and services. Implement reusable automated and AI-assisted solutions and quality practices. Build and improve frameworks and tooling that help teams detect, diagnose, and act on quality issues. Collaborate with engineering and data teams to improve software and data quality processes, tooling, and developer experience. You Offer Strong Python and SQL skills; Java experience is a plus. Understanding of data pipelines, transformation workflows and practical approaches for validating data integrity in complex systems. Hands-on experience creating, extending and maintaining automation frameworks or test tooling. Experience working with CI/CD (Gitlab or similar) pipelines and automated quality checks. Strong communication skills with a proficiency in English, every other language is a plus. It would be a plus, if you have: Experience working in data-heavy, distributed, or platform-oriented environment. Experience with Databricks or similar data platform environments. Familiarity with AWS or similar cloud providers. Familiarity with data quality concepts and tools such as SODA, Great Expectations, etc. Exposure to evaluating and validating AI-generated outputs. Please note that we will only consider candidates with a valid work permit. The salary range for this role is EUR 56,700–69,300

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