• 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

• Prepare and manage pre-stage files for backbook conversion activities • Support and execute data ingestion tasks in alignment with scheduled project events, including key mock events • Monitor and ensure data ingestion completion within defined SLA windows • Troubleshoot and resolve ingestion issues promptly to maintain data integrity and project timelines • Maintain detailed documentation of ingestion processes, schedules, and completion statuses • Proactive problem-solving approach

• 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

• 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