Lead Data Analyst - Private Equity

Title: Lead Data Analyst, Private Equity

Indexes Data Operations

No. of positions: 1

Shift: General

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 Indexes Data Operations team. The team is responsible for sourcing, validating, and maintaining critical reference and market data used in index construction and portfolio management, including Total Shares Outstanding (TSO) and Free Float data across both public and private markets. In addition to core data operations responsibilities, we work on Private Markets data and content, supporting the development of new Indexes, operational processes and index review activities. We are looking for a content researcher individual contributor with expertise in Private Equity markets. This role will play a key part in strengthening Morningstar's private markets capabilities by ensuring the quality, scalability, and integrity of data related to venture capital, private equity, private companies, and listed/unlisted investment funds. The role also requires flexibility to support other Public Equity data coverage areas, including Float and TSO datasets, collaborating with the wider team to meet delivery commitments during critical business cycles and peak demand periods. This is a mid-level individual contributor role, equivalent to an Assistant Team Lead/Team Lead level in the people manager track. The position is based in Vashi, Navi Mumbai, India.

Responsibilities:

• Own the business definition, scope, quality, sourcing strategy, operating model, and lifecycle of private-markets data used by Morningstar Indexes.
• Define and maintain the private-markets data taxonomy, business definitions, critical data elements, entity relationships, source hierarchy, curation rules, and coverage standards.
• Own the end-to-end business process for sourcing, collecting, validating, curating, approving, correcting, and maintaining private-markets data.
• Establish data-quality standards and KPIs covering accuracy, completeness, consistency, timeliness, coverage, uniqueness, and source traceability.
• Monitor data-quality performance, prioritize material issues, lead business root-cause analysis, and ensure effective corrective and preventive actions.
• Own the business roadmap for private-markets data, balancing new data coverage, quality improvements, sourcing changes, process scalability, operational risk, and index-product priorities.
• Gather and prioritize requirements from Index Research, Index Operations, Product, and other data users, translating them into clear business requirements, rules, and acceptance criteria.
• Partner with the Technology teams to deliver data-platform and workflow enhancements, while retaining accountability for business prioritization and business acceptance.
• Own business UAT and sign-off for changes affecting private-markets data, including validation of business rules, workflows, controls, and downstream usability.
• Define and manage the data-sourcing strategy, source precedence, confidence standards, and procedures for resolving conflicting information.
• Own business relationships with external data vendors and content providers, including requirements, coverage and quality assessment, performance reviews, escalations, and sourcing recommendations.
• Assess market, regulatory, and industry developments and translate relevant changes into data requirements, source changes, process updates, and roadmap priorities.
• Maintain data dictionaries, SOPs, source documentation, decision logs, curation guidance, and knowledge repositories.
• Coach analysts and data stewards on private markets concepts, quality standards, source evaluation, and operational processes.

Requirements:

Essential

• At least 5 years of relevant experience in private-markets data, financial data operations, investment research, data products, index operations, asset management, or a financial data provider.
• Demonstrated ownership of a dataset, data-content capability, data operations process, or business data product.
• Strong knowledge of private markets entities, funds, ownership structures, and valuations
• Experience defining data-quality standards, validation rules, exception processes, and operational controls.
• Experience designing or improving data-sourcing, collection, curation, and maintenance processes.
• Experience evaluating and managing external data sources or data vendors.
• Ability to develop and prioritize a business data roadmap and translate stakeholder needs into requirements and acceptance criteria.
• Working knowledge of SQL sufficient for data investigation, reconciliation, validation, and UAT.
• Working knowledge of Python sufficient to implement simple ETL pipelines.
• Strong analytical, problem-solving, prioritization, and decision-making capabilities.
• Strong stakeholder-management and influencing skills, including the ability to work effectively with research, operations, product, technology, procurement, and vendors.
• Strong written communication and documentation skills.

Preferred

• Experience with index data, benchmark construction, index reviews, or portfolio-related data.
• Familiarity with private markets data vendors, regulatory filings, company registries, and other relevant data sources.
• Understanding of data governance, source lineage, metadata, point-in-time data, corrections, and auditability.
• Experience with Agile delivery and tools such as Jira, Azure DevOps, or Confluence.
• CFA, CAIA, CA, FRM, or another relevant professional qualification.

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.

I10_MstarIndiaPvtLtd Morningstar India Private Ltd. (Delhi) Legal Entity