5+ years of experience in data engineering or related field
Proficiency in Snowflake and data pipeline development
Strong understanding of data modeling and integration techniques
Experience with unstructured data processing and transformation
Familiarity with AI and machine learning concepts
Responsibilities
Map existing data sources for AI workflows
Build and maintain workflow-specific data pipelines
Transform unstructured data into structured formats
Implement data quality checks for accuracy and completeness
Contribute reusable data back to the shared platform
Benefits
Collaborative work environment within an AI-focused team
Opportunity to work on cutting-edge AI solutions
Access to a shared platform for data and resources
Professional development opportunities in AI and data engineering
Flexible work arrangements to support work-life balance
Full Job Description
About the role
As Data Engineer in an AI Development pod you make sure each workflow's AI solutions, including models, analytics and AI agents, have the right data, in the right shape, at the right time. You work on the specific data each workflow needs, building on the shared platform from the AI Infrastructure team.
What you'll do
Map the data each workflow uses today, including systems, files, emails and spreadsheets, and design how AI solutions will get it.
Build the workflow-specific pipelines, integrations and data models that AI solutions need, using Snowflake and the shared AI platform.
Turn unstructured inputs such as statements, subscription documents and Excel workbooks into structured data that models and agents can use.
Set up data quality checks so AI solutions work from accurate, complete data, and fix data issues found during testing.
Contribute workflow data back to the shared platform so the next workflow can reuse it.
