Position Details
About this role
Lead data engineering work for Amazon Grocery Tech Foundation’s Data Platform Management team. Own data integration, reporting, analytics, and the design of scalable data models and ETL/data pipelines to deliver automated insights to business users.
Key Responsibilities
- Participate in on-call rotation to support custom reporting and analytical applications
- Lead data integration, reporting, and analytics projects
- Design and implement scalable data model and ETL processes
- Design and build next-generation data infrastructure to replace existing third-party solutions
- Collaborate cross-functionally to transform complex datasets into automated, digestible analytics deliverables
Technical Overview
Design and build scalable data modeling and ETL processes, using SQL plus Python, PySpark, and Java to extract, transform, and load data. Participate in on-call support for custom reporting applications and modernize data infrastructure, collaborating across multiple teams via Jira-managed processes.
Ideal Candidate
The ideal candidate is a mid-level Data Engineer who has led end-to-end data integration, reporting, and analytics initiatives for business stakeholders. They can design scalable data models and build ETL pipelines using SQL and languages such as Python, PySpark, and Java, with strong ownership in on-call support and continuous modernization of data infrastructure.
Must-Have Skills
Tools & Platforms
Required Skills
Hard Skills
Soft Skills
Industry & Role
Keywords for Your Resume
Deal Breakers
Must demonstrate data engineering experience with SQL, Must be able to build and maintain ETL processes and data pipelines, Must have proficiency in at least Python or PySpark and likely Java per the posting
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