Senior Data Engineer

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

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.