亚马逊Business Analyst-Automation Solution, Amazon Global Store

Data Warehouse Design, Development, Maintenance and Optimization: Architect, build and manage secure, flexible and scalable data warehouse solutions. Ensure the iterations adapt to the ever-changing global technology and new business demand. Performance Optimization: Write complex and efficient SQL queries for data manipulation, transformation, and aggregation. Optimize SQL queries to improve performance and efficiency. ETL Process Management: Design, implement, and maintain ETL (Extract, Transform, Load) processes. Ensure accurate and efficient data integration from various sources into the data warehouse and the optimal model to fit downstream usage. Data Quality and Governance: Implement data quality checks, balances, and controls to ensure the accuracy and integrity of data within the data warehouse. Co-work with Risk Control Management Team to ensure the optimal data quality and compliance. Collaboration and Support: Work closely with Global Team to ensure the data foundation is consistent with global standards and adapted to the latest technology; Co-work with other business analyst, business intelligence engineer, and other stakeholders to run the data foundation ecosystem and translate data needs to robust data solutions Continuous Improvement: Stay informed of industry trends and advancements in AWS based technologies. Recommend and implement improvements to processes and technologies to enhance data warehouse functionality and efficiency.

- Design and develop AI agents that automate workflows across product launch readiness, catalog quality management, supply chain visibility, and post-launch performance optimization - Build data pipelines and automation tools that integrate multiple data sources, enable real-time decision-making, and track key business metrics - Develop conversational AI assistant and detection systems that help business teams identify issues, prioritize actions, and improve operational efficiency at scale - Collaborate with cross-functional teams including Sourcing, Quality, Marketing, Business Management, Technology to identify automation opportunities, define use cases, and measure business impact - Continuously optimize existing automation solutions based on user feedback, operational metrics, and evolving business requirements A day in the life You'll start your day analyzing workflows and data to identify automation opportunities. You'll spend time building and testing AI agents using prompt engineering and coding tools, designing data pipelines, collaborating with business teams to refine requirements, and measuring the impact of your solutions on key metrics like launch readiness, operational efficiency, issue resolution speed, and time savings. You'll present findings to stakeholders and iterate on solutions based on feedback.

- Design and develop AI agents that automate workflows across product launch readiness, catalog quality management, supply chain visibility, and post-launch performance optimization - Build data pipelines and automation tools that integrate multiple data sources, enable real-time decision-making, and track key business metrics - Develop conversational AI assistant and detection systems that help business teams identify issues, prioritize actions, and improve operational efficiency at scale - Collaborate with cross-functional teams including Sourcing, Quality, Marketing, Business Management, Technology to identify automation opportunities, define use cases, and measure business impact - Continuously optimize existing automation solutions based on user feedback, operational metrics, and evolving business requirements A day in the life You'll start your day analyzing workflows and data to identify automation opportunities. You'll spend time building and testing AI agents using prompt engineering and coding tools, designing data pipelines, collaborating with business teams to refine requirements, and measuring the impact of your solutions on key metrics like launch readiness, operational efficiency, issue resolution speed, and time savings. You'll present findings to stakeholders and iterate on solutions based on feedback.

- Design and develop AI agents that automate workflows across product launch readiness, catalog quality management, supply chain visibility, and post-launch performance optimization - Build data pipelines and automation tools that integrate multiple data sources, enable real-time decision-making, and track key business metrics - Develop conversational AI assistant and detection systems that help business teams identify issues, prioritize actions, and improve operational efficiency at scale - Collaborate with cross-functional teams including Sourcing, Quality, Marketing, Business Management, Technology to identify automation opportunities, define use cases, and measure business impact - Continuously optimize existing automation solutions based on user feedback, operational metrics, and evolving business requirements A day in the life You'll start your day analyzing workflows and data to identify automation opportunities. You'll spend time building and testing AI agents using prompt engineering and coding tools, designing data pipelines, collaborating with business teams to refine requirements, and measuring the impact of your solutions on key metrics like launch readiness, operational efficiency, issue resolution speed, and time savings. You'll present findings to stakeholders and iterate on solutions based on feedback.