About the Role
As a Lead Software Engineer on our Data Feed Platform team (Direct – Data & Research), you will partner with product owners and engineering teams to shape the technical direction of our data engineering capability. Together, you will migrate our file-based products to a unified, cloud-native data platform — architecting highly governed data pipelines, feed generation systems, and large-scale data delivery infrastructure.
This is a senior individual contributor role reporting to the Director of Technology. You will serve as a technical thought leader for a team of engineers — owning the end-to-end data platform architecture, from ingestion and transformation through to client-facing data products. You will define best practices for data governance, data modeling, performance optimization, and data reliability across the entire product lifecycle, while mentoring engineers and fostering continuous improvement within the data engineering discipline.
If your background is in data engineering, data platform development, or building production-grade data systems at scale, this role was designed for you.
Key Responsibilities
- Lead technical direction across data feeds and the data engineering function, guiding architectural decisions across platforms.
- Collaborate with engineers on the platform consolidation strategy, migrating legacy feed products onto a unified, governed, cloud-native architecture.
- Design and implement scalable data delivery mechanisms for both file-based feeds and modern marketplace distribution platforms.
- Influence technical strategy across teams by communicating architectural vision to both technical and non-technical stakeholders.
- Core Qualifications (Must Haves)
Experience:
- 7+ years of experience in data engineering, data platforms, or distributed systems.
- Cloud Expertise: Experience with large-scale data pipelines on a major cloud platform (AWS preferred; Azure or GCP also accepted).
- SQL & Programming: Experience in SQL (Postgres, SQL Server, etc) and Python (Python 3.x).
- Technical Leadership: Ability to influence engineering direction without direct management authority, mentor engineers, and drive alignment across teams.
- Deployment: Experience with containerization (Docker, Kubernetes).
- Cloud Storage: Hands-on experience with cloud object storage (AWS S3, Azure Blob Storage, or Google Cloud Storage).
Nice to Have (Experience & Tools)
- Data Warehousing: Strong hands-on experience with modern cloud data warehouses (e.g., Snowflake, Databricks, Redshift).
- Architecture: Knowledge of data lake and Lakehouse architecture and familiarity with open table formats like Delta Lake and Apache Iceberg.
- Domain Knowledge: Previous experience in highly regulated or financial services industries with stringent data quality and delivery SLA requirements.
- AI-Assisted Development: Experience using agentic coding tools (e.g., GitHub Copilot, Claude Code, Cursor) to accelerate development workflows.
Incentive Target Percentage
12.5% AnnualMorningstar'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.
100_MstarResCanad Morningstar Research, Inc. (Canada) Legal EntitySkills Required
- 9+ years of experience in data engineering, data platforms, or distributed systems.
- Proven experience building and optimizing large-scale data pipelines on a major cloud platform (AWS preferred; Azure or GCP accepted).
- Experience with distributed or high-performance compute engines for large-scale data transformation (e.g., Spark/PySpark, DuckDB).
- Expert proficiency in SQL (Postgres, SQL Server, etc.).
- Strong development skills in Python (Python 3.x).
- Hands-on experience with modern cloud data warehouses (e.g., Snowflake, Databricks, Redshift).
- Experience with containerization and orchestration (Docker, Kubernetes).
- Hands-on experience with cloud object storage (AWS S3, Azure Blob Storage, or Google Cloud Storage).
- Demonstrated technical leadership: influence engineering direction, mentor engineers, drive cross-team alignment.
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.
