About the Role
We are looking for a Senior Software Engineer to drive the design, development, and scaling of our centralized, API-driven data validation platform. This is a hands-on individual contributor role focused on building high-performance, scalable, and intelligent validation systems that process large datasets with speed and accuracy. You will work across backend systems, validation engines, APIs, and data processing pipelines, with opportunities to contribute to AI-driven capabilities such as anomaly detection, rule automation & LLM based capabilities.
Key Skills:
• 5 to 8 years of experience into Python
• Strong proficiency in Python(data manipulation libraries like Pandas, NumPy) with writing clean, maintainable, and testable code.
• Design and develop scalable backend services for data validation.
• Implement high-throughput data processing pipelines.
• Integrate CheckMate with enterprise data systems and pipelines.
• Enable real-time and batch validation capabilities
• Design and implement - Field-level validations, Cross-field and relational rules & Schema and data integrity checks.
• Knowledge of parallel processing and asynchronous execution.
• Knowledge of caching, indexing and efficient data structures.
• Strong knowledge of API integration, and data extraction from both structured and unstructured sources
• Knowledge of distributed computing and data engineering techniques for scalable data processing
• Maintain auditability and traceability in validation workflows.
• Collaborate with Sustainalytics Data Services Digital, Client Services, Business Analysts, Data Engineers teams to deliver timely and accurate outputs.
• Good to have exposure to LLM.
• Good to have knowledge of anomaly detection using algorithms like Isolation Forest or similar.
• Good to have knowledge of SQL for querying and managing relational databases.
• Good to have Excel skills, including formulas, pivot tables, and automation techniques.
• Stay up-to-date with the latest developments in AI, and client facing technologies.
• Bachelor’s degree in Computer Engineering, Computer Science, or related field.
• Strong analytical and problem-solving skills with attention to detail.
• Ability to manage multiple priorities and deliver under tight deadlines. Preferred Skills
• Experience with data visualization tools (Power BI, Tableau).
• Familiarity with version control (Git) and workflow automation.
• Knowledge of financial data and reporting standards is a plus.
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 EntitySkills Required
- 5 to 8 years of experience in Python
- Proficiency in Python including data manipulation libraries (Pandas, NumPy) and writing clean, testable code
- Design and develop scalable backend services for data validation
- Implement high-throughput data processing pipelines
- Integrate CheckMate with enterprise data systems and pipelines
- Enable real-time and batch validation capabilities
- Design and implement field-level, cross-field, relational, and schema data integrity checks
- Knowledge of parallel processing and asynchronous execution
- Knowledge of caching, indexing, and efficient data structures
- Strong knowledge of API integration and data extraction from structured and unstructured sources
- Knowledge of distributed computing and data engineering techniques for scalable processing
- Maintain auditability and traceability in validation workflows
- Bachelor's degree in Computer Engineering, Computer Science, or related field
- Strong analytical and problem-solving skills with attention to detail
- Ability to manage multiple priorities and deliver under tight deadlines
- Exposure to large language models (LLM)
- Knowledge of anomaly detection algorithms (e.g., Isolation Forest)
- Knowledge of SQL for querying and managing relational databases
- Excel skills including formulas, pivot tables, and automation
- Experience with data visualization tools (Power BI, Tableau)
- Familiarity with version control (Git) and workflow automation
- Knowledge of financial data and reporting standards
What the Team is Saying
Morningstar Compensation & Benefits Highlights
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Leave & Time Off Breadth — Time-off policies include flexible PTO and a paid sabbatical every four years, often highlighted as a standout perk. Feedback suggests this structure supports strong work–life balance and meaningful breaks.
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Parental & Family Support — Policies advertise a global minimum of 16 weeks for primary caregivers, up to 8 weeks for secondary caregivers, and at least six weeks of paid caregiving leave. These offerings signal above-average support for family and caregiving needs.
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Retirement Support — Retirement programs feature employer 401(k) contributions/matching, with some postings citing a 75% match on up to 7% of pay. Feedback suggests these offerings are a strong pillar of the package.
Morningstar Insights
What We Do
We are a global investment research and financial data company with 40-plus offices across North America, Europe, Australia, and Asia. Our products and services are used daily by individual investors, financial advisors, asset managers, retirement plan providers, and institutional investors. We provide data, research, and analysis across managed investment products, publicly listed companies, private capital markets, debt securities, and real-time global market data. The financial system can have real barriers—hidden information, friction that can slow decisions, and forces that can limit transparency and access. We work to remove them, bringing independent research, connected data, and investor-first tools to a system that needs more clarity. The people doing this work span research, technology, design, product, sales, and functional areas. We build many of our products in-house, so the work can connect directly to the tools investors use to make real financial decisions.
Why Work With Us
Morningstar’s missing is to empower investor success. We can only do that if our people feel empowered. That means finding people who think independently, bring a wide range of backgrounds with analytical rigor and genuine intellectual curiosity to the work.
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Morningstar Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
Across most of our offices globally, employees work four days a week in the office and one day from home. We recognize that life doesn't always fit a fixed schedule and offer programs that can help provided increased workplace flexibility.
