Top eCommerce Data Engineering Jobs

This role involves designing and implementing technical solutions for enterprise systems like SAP, translating business needs into functional designs, and ensuring system performance.

The Data Engineer II role involves optimizing data architecture, developing data pipelines, and supporting analytics initiatives for cross-functional teams.

The Data Engineer will develop and maintain data pipelines and frameworks, leveraging AI tools, while ensuring compliance and operational excellence across data platforms.

The Solutions Consultant will support the implementation and QA of SDK and API integrations, assist clients with technical issues, and contribute to the development of demo environments and technical resources while gaining experience in data infrastructure.

As a Staff Data Engineer, you will lead data engineering initiatives, architect and build scalable data pipelines, and mentor teams, enhancing Crunchyroll's data infrastructure within AWS and GCP environments.

Lead the evolution of data platform by designing scalable pipelines, improving data processes, mentoring teams, and modernizing data architecture.

As a Data Engineer, you will design, implement, and maintain data systems for Notifications at Whatnot, ensuring data quality and performance while collaborating with cross-functional teams on data architecture and workflows.

Build and own end-to-end sales data pipelines and curated marts in Snowflake/dbt; implement monitoring, tests, and governance; run reverse-ETL to operational systems; partner with Sales, Ops, Finance, and People to deliver production-ready analytics products.

The Associate Data Engineering role focuses on building data solutions and pipelines, learning from senior engineers, and participating in a structured tech program.

Lead design and build of a scalable, secure cross-cloud data platform and marts. Drive selection and optimization of the modern data stack, enforce governance and lineage, and establish reusable data models and best practices to support analytics, BI, and ML use cases across product and engineering teams.