Title: Data Quality Assurance Analyst
Indexes Data Quality Assurance
The Group: Morningstar Indexes Team leverages its expertise in equity research, manager research, asset allocation, and portfolio construction to create innovative investment solutions. It uses Morningstar`s intellectual property to create indexes that empower investors’ success at every stage of the investment process - market monitoring, benchmarking, and asset allocation. The unit offers a broad suite of global equity, bond, commodity and asset allocation indexes.
The Role: Morningstar Indexes seeks an intelligent and creative professional for its Data Quality Assurance team. The primary function of the team is to own, validate and maintain research data (Price Yields, Dividend Metrics, Thematic Scores, Equity Research Data etc.) in Indexes environment. The team is also responsible for handling onboarding of new datasets, integrity of data across different databases that powers new products and maintenance platforms, regulatory compliance, and production automation. Team also source, validate and onboard Morningstar security level reference, corporate actions, float shares outstanding and other data for the construction of new index portfolios. We are looking for a person who is passionate about investing and with good knowledge about sourcing, maintaining and validating cross asset class data. This position will be in Vashi, Navi Mumbai (India).
Responsibilities:
- Ensure the quality and integrity of input data used for index development and ongoing maintenance by implementing robust validation checks and exception handling processes.
- Lead the onboarding of new datasets critical to index creation, working closely with data vendors, engineering, and research teams to ensure seamless integration.
- Perform monthly validations on Index Research Data and detect & correct data anomalies before Reconstitution process.
- Perform rigorous quality assurance on historical data, identifying anomalies and ensuring consistency across time series and asset classes.
- Conduct comprehensive UAT (User Acceptance Testing) for system enhancements, data pipelines, and validation workflows, ensuring smooth deployment into production environments.
- Develop and maintain detailed data dictionaries and interactive dashboards, enabling transparency, traceability, and enhanced stakeholder communication.
- Champion continuous improvement initiatives, identifying process inefficiencies and leading quality improvement projects to enhance data accuracy, timeliness, and system reliability.
- Proactively identify and escalate data, system, or process-related issues, collaborating cross-functionally to recommend and implement enhancements that improve data quality and operational efficiency.
Requirements:
- Bachelor’s degree in Economics, Finance, Business, or a related field; Master’s degree or progress toward a postgraduate qualification is a plus.
- Minimum of 3 years of experience in the financial domain, with a strong focus on equity data, particularly corporate actions, share data, price feeds, and reference data.
- Solid understanding of ratios and other research related data points like price yield, price multiples, moat, thematic scores etc.
- Proficient in data management policies and best practices, with hands-on experience using standard data governance and analytics tools.
- Strong interest in investing and capital markets, with a sound understanding of securities, market structures, and data flows.
- Basic to intermediate proficiency in SQL, with the ability to explore, query, and interpret database structures and relationships.
- Working knowledge of Python is a strong advantage for data automation and analysis tasks. Advanced skills in Microsoft Excel, including pivot tables, data analysis functions, and macros; familiarity with collaboration tools such as SharePoint, Teams, or JIRA.
- Progress toward the CFA charter is considered an asset and demonstrates commitment to the investment profession.
Morningstar is an equal opportunity employer.
Morningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office 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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