Position Details
About this role
Data engineering role focused on building and maintaining AWS-based data warehouse/data lake infrastructure and real-time data pipelines for Amazon's retail analytics. The candidate will work with large data sets and collaborate across teams to enable AI-driven analytics.
Key Responsibilities
- Design, implement, and support data warehouse/data lake infrastructure using AWS bigdata stack, Python, Redshift, QuickSight, Glue/lake formation, EMR/Spark, Athena
- Creation and support of real-time data pipelines built on AWS technologies
- Incremental processing of data using Iceberg and Spark
- Collaborate with other Engineering teams, Product/ Managers/SDEs to implement AI based agentic analysis
- Lead cross-team data initiatives
Technical Overview
Stack includes AWS data services (Redshift, S3, Glue, Lake Formation, EMR/Spark, Athena, Iceberg, QuickSight) with Python, SQL/PLSQL, and ETL tooling; emphasis on data modeling, warehousing, and real-time data processing.
Ideal Candidate
The ideal candidate is a mid-level data engineer with 3+ years of experience in AWS data services, data modeling, and ETL, proficient in Python and SQL, and capable of building scalable data warehouse/data lake solutions on the AWS stack.
Must-Have Skills
Nice-to-Have Skills
Tools & Platforms
Required Skills
Hard Skills
Soft Skills
Industry & Role
Keywords for Your Resume
Deal Breakers
Less than 3 years of data engineering experience, Lack of data modeling/warehousing or ETL experience, No experience with SQL or Python, No AWS data services experience
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