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Added 32 mins ago
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Morningstar

Lead Software Engineer

Toronto, ON, Canada

$93,200.00-$136,696.00 · Full-time

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Job details

Pay: $93,200.00-$136,696.00
Job type: Full-time
Experience: 7+ years of experience in data engineering, data platforms, or distributed systems.
Posting language: English
Posted: Oct 12, 2026

Original job description

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.

Base Salary Compensation Range

$93,200.00-$136,696.00

Incentive Target Percentage

12.5% Annual

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.

100_MstarResCanad Morningstar Research, Inc. (Canada) Legal Entity

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More about this job

Responsibilities

Lead the technical direction for data feed platforms and guide the migration of legacy products to a unified, cloud-native architecture. Collaborate with engineering teams to design scalable data delivery mechanisms and define best practices for data governance and performance optimization.

Requirements

Requires 7+ years of experience in data engineering, distributed systems, or cloud platforms. Candidates must have strong proficiency in Python, SQL, and experience with containerization technologies like Docker and Kubernetes.

Skills

Data engineering
Cloud platforms
SQL
Python
Distributed systems
Data governance
Data modeling
Docker
Kubernetes
AWS
Snowflake
Databricks
Data architecture
Technical leadership
Data pipelines

Benefits

Hybrid work environment

Visa sponsorship

Not detected in the job text

Keywords

Data Engineering
Cloud-native
AWS
Python
SQL
Docker
Kubernetes
Data Governance
Data Modeling
Distributed Systems
Snowflake
Databricks
Redshift
Delta Lake
Apache Iceberg
Data Lake
Lakehouse
S3
Azure Blob Storage
Google Cloud Storage
GitHub Copilot
Claude Code
Cursor
Financial Services
Data Pipelines
Architecture
Technical Leadership
SLA
Data Delivery
Platform Engineering

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