Senior Data Analyst (Customer-Centric Planning)

Posted 13 Days Ago
Be an Early Applicant
Taipei City, TWN
In-Office
Senior level
eCommerce • Fintech • Logistics • Retail
The Role
Analyze operational and customer experience data, perform ad hoc and root-cause analyses, and build customer experience funnels. Design and maintain Airflow ETL pipelines and DAGs using Presto/Hive SQL, develop data marts, monitor data quality, and create reports. Build Python automation integrating internal tools and APIs, including AI- and LLM-enabled workflows to improve reporting, quality assurance, and operational efficiency.
Summary Generated by Built In

Please complete the attached Internal Transfer Request Form and submit.   

Please make sure to apply with your Coupang e-mail address.   

   

  

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:
  1. Delve into underlying technologies: Directly operate Airflow and Presto clusters, participating in the complete lifecycle from Raw Data to Insight.
  2. Embrace new technologies: We actively introduce AI (Windsurf, Gemini, Copilot) and automation tools to eliminate repetitive tasks.

  

What You Will Do 

  • Quickly support (within hours) and respond to the needs of various operational teams, formulate Ad-Hoc analysis plans, and produce high-quality, highly accurate data reports.
  • 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.
  • Familiar with Tableau Server, Power BI, or related report creation and operation.

  

Preferred Qualifications


  • Familiar with customer service and ticketing system operational data structures: experience in data analysis for similar systems such as customer service, e-commerce, and logistics.
  • 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.
  • Familiar with version control tools (GitHub/Git), accustomed to Pull Request (PR) review and collaboration processes.
  • AI/LLM application experience: experience using LangChain or internal AI tools to build auxiliary analysis agents or automated processes.

Skills Required

  • 3+ years of data analysis or data engineering experience
  • Ability to write complex SQL queries, including recursive CTEs, window functions, and JSON parsing
  • Business analysis skills for translating ambiguous business problems into data analysis projects
  • Experience creating and operating reports with Tableau Server, Power BI, or a related reporting tool
  • Experience analyzing customer service, e-commerce, or logistics operational data
  • E-commerce or supply chain domain knowledge, including logistics and inventory logic
  • Practical Python development experience for automation scripts, API integrations, or data transformation
  • Experience writing and maintaining Airflow DAGs or using similar workflow scheduling tools
  • Experience with Git or GitHub, pull request reviews, and collaborative development
  • Experience using LangChain or internal AI tools to build analysis agents or automated processes
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The Company
108,000 Employees
Year Founded: 2010

What We Do

Coupang is a U.S. technology and global commerce company founded in 2010, operating online retail and cross-border commerce, restaurant delivery, video streaming, and fintech/payment services. Through brands including Coupang, Eats, Play, Rocket Now, and Farfetch, it uses technology, logistics, and fulfillment infrastructure to serve millions of customers in Korea, Taiwan, the United States, and more than 190 countries and territories worldwide.

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