Data Engineering Lv.4

Overview

Build and manage analytics and production data ETL/ELT systems for high-volume data ingestion, and enable reliable, accurate logging and data usage across the PPE domain.

What you'll do

• Build and manage analytics and production data ETL/ELT systems for high volume data ingestion from diverse sources.
• Partner with Data Science, Engineering, and Product to enable reliable, accurate logging/implementation and usage across the PPE domain.
• Ensure data quality, observability, and reliability across the data lifecycle.
• Create and maintain dashboards and reporting infrastructure to surface key PPE metrics to stakeholders.
• Optimize systems for performance, cost efficiency, and scalability.
• Leverage LLMs and advanced prompt engineering to automate and extract insights from unstructured data, and accelerate internal analytical workflows.
• Define and manage SLAs for data systems.

What you'll need

• 3+ years of relevant working experience in a data engineering or business intelligence role.
• Proficiency in Data modelling, SQL and Python.
• Experience building and maintaining data pipelines (ETL/ELT) at scale.
• Experience in data storytelling using PowerBI, Tableau, or similar tools to communicate insights effectively to nonexperts.
• Bachelor's degree in Computer Science or equivalent.

Nice to have

• Hands-on experience with version control (GitHub), workflow orchestration, and ETL scheduling tools (e.g. Airflow, Dagster, DBT).
• Experience with distributed storage systems (e.g., HDFS, S3).
• Familiarity with prompt engineering and using generative AI tools to solve data problems or automate content generation.
• Previous experience in e-commerce or retail domains.
• Working knowledge of statistics and ML techniques.

Details

• Work model: Hybrid.
• Internal transfer: apply with your Coupang e-mail address using the Internal Transfer Request Form.