Principal Software Engineer
Offre en anglaisThe Principal Software Engineer will lead the migration of legacy products to a unified, cloud-native data platform while architecting highly governed data pipelines. They will also serve as a technical thought leader, defining best practices for data modeling, performance optimization, and data reliability across the product lifecycle.
- Hybride
- Toronto, ON
- Publié 14 août 2026
- 1 poste
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Résumé du poste
The Role 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. Job 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. Qualifications Experience: 9+ years of experience in data engineering, data platforms, or distributed systems. Cloud Expertise: Proven track record building and optimizing large-scale data pipelines on a major cloud platform (AWS preferred; Azure or GCP also accepted). Data Processing at Scale: Strong experience with distributed or high-performance compute engines for large-scale data transformation. Familiarity with frameworks such as Spark/PySpark, DuckDB, or similar modern engines, and the ability to evaluate trade-offs between them for different workloads. SQL & Programming: Expert proficiency in SQL (Postgres, SQL Server, etc) and strong development skills in Python (Python 3.x). Data Warehousing: Strong hands-on experience with modern 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: 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) Architecture: Knowledge of data lake and lakehouse architecture, including the implementation and use of 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 $112,583.00-$162,125.00 Incentive Target Percentage 20% 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
Ce que vous ferez
The Principal Software Engineer will lead the migration of legacy products to a unified, cloud-native data platform while architecting highly governed data pipelines. They will also serve as a technical thought leader, defining best practices for data modeling, performance optimization, and data reliability across the product lifecycle.
Exigences
Candidates must have 9+ years of experience in data engineering or distributed systems with expert proficiency in Python and SQL. Strong hands-on experience with cloud data warehouses and major cloud platforms like AWS is required.
Avantages
• Hybrid work environment • Professional development resources
Compétences indiquées
- KubernetesSouhaitée
- SQLSouhaitée
- CI/CDSouhaitée
- DockerSouhaitée
- Amazon Web ServicesSouhaitée
- PythonSouhaitée
Autres compétences pertinentes
Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.
- Data Engineering
- Cloud Architecture
- Python
- SQL
- Spark
- PySpark
- Snowflake
- Databricks
- AWS
- Data Governance
- Data Modeling
- CI/CD
- Docker
- Kubernetes
- Distributed Systems
- Technical Leadership
- Claude Code
- Data Lakes
- Influencing Skills
- GitHub Copilot
- Technical Strategy
- Cloud-Native Architecture
- Domain Knowledge
- Cloud-Native Computing
- Apache Iceberg
- Influencing Without Authority
- DataOps
- Workflow Management
- Platform Design And Development
- Snowflake (Data Warehouse)
- Azure Blob Storage
- Thought Leadership
- Research
- Artificial Intelligence
- Amazon Web Services
- Amazon S3
- Microsoft Azure
- Management
- Containerization
- Communication
- Data Processing
- Continuous Improvement Process
- Data Transformation
- Data Quality
- Data Warehousing
- Financial Services
- Google Storage
- Scalability
- Python (Programming Language)
- PostgreSQL
Domaines d’emploi
- Technology
- Data & Analytics
- Software
- Engineering
- Finance & Accounting
- Principal Software Engineer
- Software Developer / Engineer
- Software Developers
Renseignements supplémentaires
- Expérience minimale
- 10+ ans
- Langue de l’offre
- anglais
- Heures de travail
- 40 heures par semaine
- Présence au bureau
- 4 jours par semaine