Data Quality Assurance Engineer

About Morningstar: Morningstar is a leading global provider of independent investment insights, serving both individual and institutional investors across public and private markets. Our offerings include a wide range of data, research, and investment management services, with $300+ billion in assets under management. Operating in 32 countries, Morningstar supports financial advisors, asset managers, retirement plan providers, and more with comprehensive investment solutions..
The Role: Data quality plays a crucial role in ensuring accurate insights and decision-making in financial services. As a Senior Data Quality Assurance Engineer, you will be responsible for developing and maintaining advanced data quality frameworks to ensure the accuracy, integrity, and consistency of financial and investment datasets.
This role goes beyond traditional data validation-it involves leveraging AI/ML-based anomaly detection, designing statistical validation processes, and implementing automation-driven data governance. You will work closely with data engineers, analysts, and business stakeholders to embed quality assurance throughout the data lifecycle. Additionally, you will play a critical role in identifying emerging trends and proactively addressing data challenges in a fast-paced, highly regulated industry.
Morningstar offers a dynamic and collaborative work environment that encourages innovation and professional growth. You will have the opportunity to work with cutting-edge AI, automation, and cloud technologies, while contributing to industry-leading financial insights used by professionals worldwide.
What You'll Do / Responsibilities• Develop and implement scalable data quality frameworks that integrate with data pipelines and analytics platforms.• Design and execute advanced statistical validation techniques to detect anomalies and inconsistencies across datasets.• Implement AI/ML-based data quality checks, leveraging predictive models to identify patterns and improve data integrity.• Lead root cause analysis efforts for data discrepancies, working cross-functionally to drive permanent solutions.• Collaborate with data engineers and business stakeholders to enhance data cleansing, transformation, and governance practices.• Monitor, report, and continuously optimize data quality KPIs through automated dashboards and reporting tools.• Ensure compliance with industry regulations and data governance policies, supporting audits and regulatory initiatives.• Contribute to the continuous improvement of data quality processes, integrating automation, cloud, and AI-driven innovations.
Who You Are / Requirements / Qualifications• Proficient in SQL and Python, with experience in data analysis, ETL processes, and database optimization.• Hands-on experience with AI/ML techniques for anomaly detection, trend analysis, and predictive modeling.• Strong knowledge of statistical analysis methods, including hypothesis testing and data validation.• Experience with automation tools and test frameworks for data validation in cloud and big data environments.• Detail-oriented with a passion for problem-solving, capable of identifying and resolving complex data issues.• Excellent collaboration and communication skills, with experience working in cross-functional and international teams.• Familiarity with financial services and investment data structures is a strong advantage.• Fluent in English (additional European languages are a plus).
Why join us? • Work with cutting-edge technologies in AI, automation, and cloud-based data management.• Be part of a global, mission-driven organization that values data integrity and financial transparency.• Collaborate with top talent across Europe and beyond, in an innovative and inclusive work environment.• Flexible work arrangements with opportunities for professional development and growth.• Competitive salary and benefits package, tailored for the European market.
Ready to Shape the Future?
At Morningstar, every hire strengthens our mission to empower investor success. Apply now and help shape the future of data-driven investing with us.
Morningstar's hybrid work environment gives you the opportunity to work remotely and collaborate in-person each week. We've found that we're at our best when we're purposely together on a regular basis, at least three days each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.
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