Data Quality Assurance Analyst

What we do:
Morningstar is a financial services company committed to helping people achieve financial security through trusted investment research and data. Our Managed Investment Data (MID) team plays a crucial role in this mission by working directly with asset management companies, which send us comprehensive data on their funds. This data includes information on portfolios, ownership stakes, investment styles, NAVs (net asset values), holdings, and operations. Our team's responsibility is to collect, organize, and standardize this data, adding value with Morningstar's own analytics to help investors make better-informed decisions.
The work of the MID team supports individual investors, financial advisors, and institutional clients by ensuring they have access to clear, accurate, and compliant investment data across Morningstar's software and data platforms. Since 2020, the team has grown significantly, expanding from just five people to over 380. This growth reflects the increasing importance of our work and the high demand for reliable managed investment data in the financial industry. By managing new fund activations and essential documentation, the MID team helps ensure data accuracy and regulatory compliance, which are essential for effective fund management and supporting the broader financial ecosystem.
Job Description:
The Quality Assurance Analyst is responsible for maintaining the quality and reliability of data through audits, reviews, and operational assessments. This role focuses on monitoring data processes, conducting manual and semi-automated audits, and enhancing operational efficiency. The candidate will collaborate closely with operations, data management, and governance teams to uphold high data quality and compliance standards. Success in this role requires keen attention to detail, strong auditing skills, and the ability to drive operational improvements without deep technical involvement.
Key Roles & Responsibilities:

• Conduct research on complex projects to develop actionable recommendations and solutions.
• Collaborate with global teams across multiple functions to identify user needs and ensure the accuracy, timeliness, and completeness of key data universes, aligning with established operational standards and definitions.
• Actively participate in global and local calls and meetings, maintaining effective communication with teams such as MID operations, methodology, project teams, and management.
• Perform broad-scope audits to identify anomalies or outliers that deviate from established logic.
• Conduct end-to-end analysis to determine the root causes of anomalies and validate results.
• Provide structured recommendations, including verbal and written feedback, to the Calculation team for logic modifications.
• Implement lean practices across the value stream to optimize performance and drive continuous improvement in the audit process, leveraging Lean Six Sigma and other process improvement methodologies.
• Track, measure, and report key daily, monthly, and quarterly metrics to stakeholders.
• Analyze client feedback, emails, and responses to ensure factual accuracy.
• Review client requirements and collaborate with Operations to ensure they are effectively addressed.
• Continuously evaluate processes and identify opportunities for improvement.

Required Competencies:

• Bachelor's or master's degree in finance or business with a strong academic background. Lean Six Sigma Green Belt certification is preferred.
• Over five years of professional experience in progressively responsible roles, including data collection and quality control.
• Strong knowledge of finance and accounting, with a problem-solving mindset grounded in statistical analysis.
• Proven project management skills, including leading large-scale data quality initiatives and presenting findings to senior leadership.
• Experience managing multiple projects in a fast-paced, dynamic environment with evolving priorities.
• Excellent communication, interpersonal, and project management abilities.
• A lean mindset focused on maximizing value, minimizing waste, and fostering a culture of continuous improvement.
• Passion for data research, investing, and data management.
• Strong analytical skills to research and evaluate information for informed decision-making.
• Prior experience leading teams of 10 or more is a plus.
• Demonstrated ability to mentor and develop talent.
• Proficiency in Power BI, VBA, SQL, Python, and PostgreSQL is an added advantage.

Morningstar is an equal opportunity employer.
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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