Data Engineer I: Build Global Data Platform & ETL

Amazon.com Services LLC; Austin (TX); On-site; USD 75,000 - 110,000; Full time

Job summary

Amazon.com Services LLC in Austin, TX is seeking a Data Engineer I to design and build scalable data platforms that empower analytics across the GEIST program. You will work with AWS data services and collaborate with cross-functional teams to deliver reliable data infrastructure.

This role focuses on data warehousing, ETL development, and real-time data pipelines, with opportunities to advance the platform for internal customers and global teams.

Qualifications

• 1+ years of data engineering experience.
• Experience with data modeling, warehousing and ETL pipelines.
• Experience with one or more query languages (e.g., SQL, HiveQL, SparkSQL).
• Experience with one or more scripting languages (e.g., Python, Shell).

Responsibilities

• Design, implement, and support data warehouse / data lake infrastructure using AWS bigdata stack, Python, Redshift, QuickSight, Glue/lake formation, EMR/Spark, Athena etc.
• Develop and manage ETLs to source data from various systems and create unified data model for analytics and reporting.
• Creation and support of real-time data pipelines built on AWS technologies including EMR, Glue, Redshift/Spectrum and Athena.
• Continual research of the latest big data technologies to provide new capabilities and increase efficiency.
• Manage numerous requests concurrently and strategically, prioritizing when necessary.
• Partner/collaborate across teams/roles to deliver results.

Skills

Data engineering

Data modeling

ETL pipelines

SQL

Python

AWS

Tools

AWS stack

Redshift

EMR

Glue

S3

Job description

Amazon.com Services LLC in Austin, TX is seeking a Data Engineer I to design and build scalable data platforms that empower analytics across the GEIST program. You will work with AWS data services and collaborate with cross-functional teams to deliver reliable data infrastructure.

This role focuses on data warehousing, ETL development, and real-time data pipelines, with opportunities to advance the platform for internal customers and global teams.