- Build and own end-to-end data pipelines in Snowflake — from raw ingestion through transformation to serving layers for AI products
- Partner with ML engineers and data scientists to build and maintain AI-specific data infrastructure
- Consolidate fragmented data sources across the organization into reliable, automated pipelines
- Design scalable data models and marts that serve both analytics and ML feature engineering
- Support rapid iteration on new data products and features in a fast-moving environment
- Collaborate cross-functionally with analytics, data science, and product teams to translate requirements into data solutions
- Proactively monitor and resolve data quality issues, optimizing for cost and performance
- Employ AI technologies to enhance and optimize business processes
- Utilize and leverage Power Digital's Nova ecosystem as it relates to your department
- Use AI coding tools as part of your daily development workflow to accelerate pipeline development and data quality work
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