This job is with Morningstar, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. As a Principal 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.

Location: Toronto, ON (Hybrid-4 days in Office)

We intentionally prioritize in-person collaboration, as we've found it strengthens creative quality, alignment, and team momentum.

Lead and provide deep technical direction across data feeds and the data engineering function, guiding architectural decisions across platforms.





Design and implement scalable data delivery mechanisms for both file-based feeds and modern marketplace distribution platforms.

Drive DataOps maturity by establishing comprehensive data quality, monitoring, alerting, and CI/CD practices across the platform.

Influence technical strategy across teams by communicating architectural vision to both technical and non-technical stakeholders.

9+ years of experience in data engineering, data platforms, or distributed systems.

Proven track record building and optimizing large-scale data pipelines on a major cloud platform (AWS preferred; Data Processing at Scale: Strong experience with distributed or high-performance compute engines for large-scale data transformation.

SQL & Programming: Expert proficiency in SQL (Postgres, SQL Server, etc) and strong development skills in Python (Python 3.Data Warehousing: Strong hands-on experience with contemporary cloud data warehouses (e.g., Snowflake, Databricks, Redshift).

Technical Leadership: Demonstrated ability to influence engineering direction without direct management authority, mentor engineers, and drive alignment across teams.

Deployment: Hands-on experience with cloud object storage (AWS S3, Azure Blob Storage, or Google Cloud Storage).

Knowledge of data lake and lakehouse architecture, including the implementation and use of open table formats like 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., In most of our locations, our hybrid work model is four days in-office each week. Canada) Legal Entity

📌 Principal Software Engineer Data / Analytics (Toronto)
🏢 Morningstar
📍 Toronto