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.