Role: Quantitative Developer
Location: Mumbai/ Delhi (4 days working from office)
Shift: UK Shift (Afternoon Shift) (2:00pm to 11:00pm)
The Area: The Research & Investment group is a global team guided by Morningstar’s investment principles focused on delivering great long-term investment results to help end-investors reach their financial goals. We use our expertise in asset allocation, investment selection and portfolio construction to create world-class investment strategies leveraging the full resources of Morningstar. The group specializes in multi-asset investing, using building blocks in equities, fixed income and alternative investments to construct robust portfolios. Through our investment offerings, we serve financial advisers and institutions, and the investors that they serve.
Role Summary:
The Quantitative Developer will join the Systematic Strategies team in the Research & Investment group. This experienced professional will build scalable research infrastructure used by portfolio managers and quantitative researchers to develop, back test, and deploy multi asset models.
You should understand the nuances of the data and prepare it for ingestion, and your daily work with researchers and portfolio managers will facilitate the research, design, and deployment of investment strategies.
This role is ideal for someone who thrives at the intersection of data engineering, cloud architecture, and financial systems.
Key Responsibilities:
The successful candidate will
- Design and maintain scalable data pipelines for market, fundamental, and alternative datasets using Python, PySpark, FastAPI and AWS
- Build and support investment data platforms, maintain databases and research datasets.
- Integrate and automate data retrieval from internal/external providers such as FactSet, Morningstar, Axioma, and other third-party sources
- Collaborate with quantitative researchers and portfolio managers to support enhancement of production workflows
- Automate operational processes through workflow orchestration, CI/CD, and Infrastructure-as-Code practices
- Exposure to streaming data services and event-driven architectures used for real-time data ingestion, processing, and distribution
- Evaluate and leverage AI/ML and Generative AI technologies to enhance analytics and operational efficiency
Requirements:
- Strong expertise in Python, PySpark, and distributed data processing
- Experience with Airflow, EMR, AWS Step Functions, Docker, Git, CI/CD, Terraform, and CloudFormation
- Strong SQL skills and experience with Redshit, Athena, DataLake and Parquet
- Experience of building AI agents & agentic workflow is desirable and will be considered a strong plus
- Experience with handling financial data from vendors such as FactSet, Bloomberg, Morningstar, or Compustat
- Exposure to portfolio analytics, risk modelling, performance attribution, and platforms such as Axioma, MSCI Barra, Bloomberg PORT, or similar solutions
Required Technical Skills
- Advanced SQL, Python and PySpark
- Experience with creating Data Pipelines
- Exposure to cloud-based services, AWS (preferred)
- Exposure to AI-powered productivity and development tools such as ChatGPT, Microsoft Copilot, and GitHub Copilot
Preferred Qualifications
- Bachelor’s or master’s degree in engineering, Computer Science, Finance, Mathematics, Statistics, or a related quantitative discipline
- 2+ years of experience in Quantitative Engineering, Data Engineering, or Platform Engineering within investment management or financial services
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
- Advanced Python, PySpark, SQL, and distributed data processing experience
- Experience creating scalable data pipelines
- Experience with Airflow, EMR, AWS Step Functions, Docker, Git, CI/CD, Terraform, and CloudFormation
- Experience with AWS or other cloud-based services
- Experience handling financial data from vendors such as FactSet, Bloomberg, Morningstar, or Compustat
- Exposure to portfolio analytics, risk modelling, performance attribution, and platforms such as Axioma, MSCI Barra, Bloomberg PORT, or similar
- Experience using AI-powered productivity and development tools such as ChatGPT, Microsoft Copilot, and GitHub Copilot
- Experience building AI agents and agentic workflows
- Bachelor’s or master’s degree in engineering, computer science, finance, mathematics, statistics, or a related quantitative discipline
- Two or more years of experience in quantitative engineering, data engineering, or platform engineering within investment management or financial services
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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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.
