Senior Data Analyst (Catalog)

Company Introduction We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did I ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we are collectively disrupting the multi-billion-dollar commerce industry from the ground up and establishing an unparalleled reputation for being leading and reliable force in South Korean commerce. We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurs surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day. Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world. Role Overview The Catalog team plays a pivotal role in delivering a seamless eCommerce experience, as it directly shapes how customers discover and purchase products online. This role combines senior-level business analysis with strong data engineering expertise. The position focuses on designing scalable data solutions, building and maintaining robust data pipelines, and delivering actionable insights to support business decision-making. The ideal candidate is equally comfortable translating business needs into data requirements and implementing reliable, efficient backend data systems. What You Will Do Business Partnership & Solution Design -Collaborate closely with catalog and cross-functional business teams to translate requirements into data models, pipelines, and dashboards. -Provide analytical support through ad hoc deep dives to identify drivers of catalog-related issues and opportunities. -Partner with external teams on special projects to investigate and mitigate business challenges. Data Engineering & Pipeline Development -Design, build, and maintain scalable ETL/ELT pipelines and data lake architecture. -Develop new data ingestion pipelines, including integrating external/vendor APIs using Python. -Ensure reliability of data systems by monitoring pipelines, troubleshooting failures, and restoring services. Data Quality & Governance -Implement robust data quality checks and validation rules to prevent downstream data issues. -Maintain and enhance core data tables to ensure accuracy, consistency, and usability. -Update and manage data lineage documentation to clearly map data flow from source to consumption layers. Performance Optimization -Optimize data processing and warehouse efficiency by rewriting and tuning SQL queries (e.g., in Snowflake or BigQuery). -Continuously identify opportunities to improve existing data tools, queries, and workflows to reduce cost and improve performance. Scalable Analytics Enablement -Build self-serve, scalable data solutions that empower stakeholders and accelerate analytics. -Automate recurring processes to improve efficiency and reduce manual effort. Continuous Improvement -Stay current with evolving data technologies, tools, and industry best practices. -Proactively identify opportunities to enhance data infrastructure and analytical capabilities. Basic Qualifications Strong business analysis and problem-solving skills with the ability to connect data to business impact Proven experience in data engineering (ETL/ELT pipelines, data modeling, and data architecture) Advanced SQL skills with experience optimizing queries in modern data warehouses (e.g., Snowflake, BigQuery) Proficiency in Python for data processing and API integrations Experience with data quality frameworks and monitoring tools