Data Engineer, Amazon Customer Service
# Data Engineer, Amazon Customer Service **Amazon.com Services LLC** · Seattle, Washington, USA · `On-site` · `full-time` 🕒 **Статус:** *Опубликовано: вчера* · *Источник: Amazon* --- ### Top Skills & Match 🎯 **Ключевой стек роли:** `[Database Administration]` `[Data Engineering]` --- ### About the Role Amazon's Customer Service (CS) organization is looking for a Data Engineer II to design, build, and optimize data solutions that power analytics and decision-making across our business. You will work on significant datasets and mid-size data solutions within the team's architecture, creating coherent logical data models and data pipelines that drive self-service access to data. As a Data Engineer, you will independently own data design end-to-end — from ingesting and modeling semi-structured and structured data to building performant, well-tested pipelines that serve business-critical reporting and analytics use cases. You'll partner with SDEs, BIEs, Data Scientists, and Product Managers to understand data needs, propose solutions, and deliver datasets that enable stakeholders to make data-driven decisions. Key job responsibilities - Design and implement logical and physical data models for complex datasets, driving downstream analytics and self-service BI infrastructure - Build and optimize data pipelines (ETL/ELT) for difficult and large-scale datasets using technologies such as AWS Glue, Spark, Redshift, and EMR - Own ongoing data quality — establish SLAs, define data certification, and build monitoring/alerting for pipeline health - Improve self-service access to data; build tools for data lineage tracking, discoverability, and governance - Automate manual processes and improve code quality, dependency management, and operational excellence - Partner with SDEs and other engineers to integrate data solutions into broader team architecture - Balance customer requirements with team technical strategy and long-term maintainability - Mentor and develop peers; participate in hiring and technical assessments - 3+ years of data engineering experience - 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience - 1+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies experience - 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience - Bachelor's degree or foreign equivalent in Computer Science, Engineering, Information Systems, Mathematics, or a related field
- Database Administration
- Data Engineering
Наблюдалась 2026-09-15, впервые 2026-09-15, источник — Amazon.