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About the Role

As a Principal Software Engineer on the Data Feed Platform team, you will partner with product owners and engineering teams to shape the technical direction of our data engineering capability. You will migrate 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 where you will serve as a technical thought leader, owning the end-to-end data platform architecture and defining best practices for data governance, modeling, performance optimization, and reliability. You will also mentor engineers and foster continuous improvement.

Responsibilities

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

Requirements

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; Azure or GCP also accepted).
Strong experience with distributed or high-performance compute engines for large-scale data transformation.
Expert proficiency in SQL (Postgres, SQL Server, etc).
Strong development skills in Python (Python 3.x).
Strong hands-on experience with modern cloud data warehouses (e.g., Snowflake, Databricks, Redshift).
Demonstrated ability to influence engineering direction without direct management authority, mentor engineers, and drive alignment across teams.
Experience with containerization (Docker, Kubernetes).
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 Delta Lake and Apache Iceberg.
Previous experience in highly regulated or financial services industries with stringent data quality and delivery SLA requirements.
Experience using agentic coding tools (e.g., GitHub Copilot, Claude Code, Cursor) to accelerate development workflows.

Skills

Data Engineering
Data Platforms
Distributed Systems
Cloud-native architecture
Data Pipelines
Data Governance
Data Modeling
Performance Optimization
Data Reliability
DataOps
Data Quality
Monitoring
Alerting
CI/CD
SQL
Python
Spark/PySpark
DuckDB
Snowflake
Databricks
Redshift
Docker
Kubernetes
AWS S3
Azure Blob Storage
Google Cloud Storage
Data Lake Architecture
Lakehouse Architecture
Delta Lake
Apache Iceberg

Location

Toronto, ON

Work Type

Hybrid (4 days in Office)

Experience Level

9+ years
Senior

Salary/Compensations

$112,583.00 - $162,125.00
Incentive Target Percentage 20%

Benefits

A range of other benefits are also available to enhance flexibility as needs change.

About the Company

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.
No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.
Morningstar Research, Inc. (Canada)

Equal Opportunity

Morningstar is committed to working with and providing reasonable accommodation to individuals with disabilities.
Morningstar is an E-Verify program participant.
Morningstar is strongly committed to creating and preserving equal opportunity for all employees and applicants.
We make all employment decisions—including recruitment, hiring, compensation, training, promotion, transfer, discipline, termination, and other personnel matters—without regard to race, color, ancestry, religion, sex, national origin, age, disability, protected veteran status, marital status, sexual orientation, genetic information, citizenship, gender identity and expression, parental status, or other legally protected characteristics or conduct.