Senior Data Analyst (Customer-Centric Planning)

Role Overview The Customer-Centric Planning team is looking for a Senior Data Analyst with an engineering mindset. You will not only be a user of data but also a builder of data infrastructure. This position highly integrates Data Analysis and Analytics Engineering. You will be responsible for maintaining Airflow ETL processes from multiple internal data sources such as Zendesk, WMS (Warehouse Management System), and OMS (Order Management System), and utilizing Python and AI tools for automation development to support the operation and optimize the experience of teams such as Supplier Support, Customer Support, and Andon. This is not just a "report-running" job. In the Customer-Centric Planning team, you will:

- End-to-End Data Pipeline Construction and Maintenance (ETL & Pipeline): Using Presto/Hive SQL to process large-scale data, responsible for designing and maintaining Airflow DAGs, developing and optimizing Data Marts, monitoring data pipeline health, and ensuring data quality. - Process Automation and Tool Development (Automation & Tooling): Using Python to develop automation scripts, integrating Slack, GitHub, Zendesk, Tableau, Presto, Confluence, and various internal APIs, and using/introducing LangChain, MCP Server to achieve automated updates and releases for various research, report generation, Quality Assurance, etc., reducing manual intervention and improving team efficiency. Basic Qualifications

- Possess e-commerce or supply chain domain knowledge: understanding of e-commerce business models and logistics inventory logic. - Possess practical Python development skills, capable of writing automation scripts, handling API integration, or performing data transformation. - Familiar with Airflow or similar workflow scheduling tools, with practical experience in writing and maintaining DAGs.

- Operational Pain Point Analysis and Root Cause Analysis: Building a customer experience funnel, identifying process issues and operational problems from the user lifecycle, and analyzing deep-seated causes. - End-to-End Data Pipeline Construction and Maintenance (ETL & Pipeline): Using Presto/Hive SQL to process large-scale data, responsible for designing and maintaining Airflow DAGs, developing and optimizing Data Marts, monitoring data pipeline health, and ensuring data quality. - Process Automation and Tool Development (Automation & Tooling): Using Python to develop automation scripts, integrating Slack, GitHub, Zendesk, Tableau, Presto, Confluence, and various internal APIs, and using/introducing LangChain, MCP Server to achieve automated updates and releases for various research, report generation, Quality Assurance, etc., reducing manual intervention and improving team efficiency.

Basic Qualifications - 3+ years of data analysis or data engineering experience, with the ability to handle complex SQL queries (Recursive CTE, Window Functions, JSON parsing). - Possess business analysis sensitivity, capable of transforming vague business problems (e.g., "Why are customer complaints increasing?") into concrete data analysis projects.

- Possess business analysis sensitivity, capable of transforming vague business problems (e.g., "Why are customer complaints increasing?") into concrete data analysis projects. - Familiar with Tableau Server, Power BI, or related report creation and operation. Preferred Qualifications

- Possess practical Python development skills, capable of writing automation scripts, handling API integration, or performing data transformation. - Familiar with Airflow or similar workflow scheduling tools, with practical experience in writing and maintaining DAGs. - Familiar with version control tools (GitHub/Git), accustomed to Pull Request (PR) review and collaboration processes.