Senior Data Engineer

Morningstar Credit Ratings, LLC; Toronto; Hybrid; CAD 90,000 - 133,000; Full time

Benefits offered by this job

Hybrid work model

Incentive plan

Job summary

Morningstar Credit Ratings, LLC is seeking a Senior Data Engineer to design and implement scalable, end-to-end data engineering solutions. The candidate should have 5+ years of experience with Snowflake, modern data pipelines, cloud platforms, and AI-enabled data solutions.

Key responsibilities include building Snowflake pipelines, Medallion Architecture, Python/Informatica data ingestion, data modeling, and deploying CI/CD for data pipelines.

Qualifications

• Minimum 5+ years of experience in data engineering or related roles.
• Strong hands-on experience with Snowflake, including data modeling 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 solid data warehousing knowledge.
• Hands-on Snowflake AI/ML capabilities (Cortex/LLM) exposure is a plus.
• Experience using Git/Bitbucket for version control in teams.
• Basic to intermediate understanding of CI/CD pipelines and deployment workflows.
• Hands-on experience with AWS cloud services and cloud-based data architectures.

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 scalable data management.
• Develop data ingestion pipelines using Python and/or Informatica to load data into Snowflake.
• Build scalable data models and transformation logic within Snowflake.
• Leverage Snowflake AI/ML capabilities to enable advanced analytics and data-driven insights.
• Manage SQL scripts, Python code, and Snowflake objects in a structured way.
• Use Git/Bitbucket for version control of Snowflake scripts, Python code, and deployment artifacts.
• Support CI/CD and deployment processes for data pipelines and database changes.
• Monitor, troubleshoot, and optimize data pipelines across environments.
• Ensure data quality, consistency, and performance across pipelines.

Skills

Snowflake

Python

SQL

Data modeling

Data pipelines

Tools

Informatica

Git/Bitbucket

CI/CD tooling

AWS

Job description

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.

Base Salary Compensation Range $90,489.00-$132,711.00 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 Morningstar is a global independent investment research and financial data company. Here, you'll help uncover what’s hidden, simplify what’s complex, and create insights that empower investor success.

Company overview Morningstar Development Program

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.