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Toronto, Ontario, Canada
Onsite
The Role:
We are looking for a Senior Data Engineer with a minimum of 5+ years of experience in designing and implementing scalable, end-to-end data engineering solutions. The ideal candidate should have strong hands-on expertise in Snowflake, modern data pipeline development, cloud platforms, version-controlled development practices, and AI-enabled data solutions.
Key Responsibilities:
Design, build, and maintain end-to-end data pipelines with Snowflake as the primary data warehouse.
Implement and support Medallion Architecture within Snowflake for structured and scalable data management.
Develop data ingestion pipelines using Python and/or Informatica to load data into Snowflake.
Build scalable and efficient data models and transformation logic within Snowflake.
Leverage Snowflake AI/ML capabilities (e.g., Snowflake Cortex, AI functions, or LLM integrations where applicable) to enable advanced analytics, automation, and data-driven insights.
Manage SQL scripts, Python code, and Snowflake objects in a structured and maintainable way.
Use Git / Bitbucket for version control of Snowflake scripts, Python code, and deployment artifacts.
Support and implement CI/CD and deployment processes for data pipelines and database changes.
Monitor, troubleshoot, and optimize data pipelines across all environments.
Ensure data quality, consistency, and performance across all pipelines.
Required Skills & Experience:
Minimum 5+ years of experience in data engineering or related roles.
Strong hands-on experience with Snowflake, including data modeling, performance tuning, and production workloads.
Proven experience in building end-to-end data pipelines.
Strong proficiency in Python for data processing and automation.
Experience with Informatica or similar ETL tools.
Advanced SQL skills with strong understanding of data warehousing concepts.
Hands-on experience with Snowflake AI/ML capabilities (e.g., Snowflake Cortex, LLM-based features, or similar AI-driven data platforms).
Experience using Git / Bitbucket for version control in collaborative environments.
Basic to intermediate understanding of CI/CD pipelines and deployment workflows.
Hands-on experience with AWS cloud services and cloud-based data architectures.
Nice to Have:
Exposure to Agile/Scrum development environments.
Knowledge of Terraform / Infrastructure as Code.
Exposure to Tableau or other BI / data visualization tools.
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.
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