New See where your enterprise data creates delays, rework, and leakage.Get a free Data Savings Estimate
Stargo

limitedDistribution · Industry Research

Data Engineer, AppStar Data Analytics & Engineering

As a Data Engineer on the AppStar DNA team, you will build and maintain data pipelines and infrastructure that support the AppStar organization. You will work across multiple data domains to develop the data infrastructure that powers analytics and reporting.

Amazon.jobs StaffMarch 26, 20261 min read
Data Engineer, AppStar Data Analytics & Engineering

Amazon's AppStar team is revolutionizing data infrastructure to enhance analytics and reporting capabilities across e-commerce platforms.

Executive Summary

Are you passionate about building data infrastructure that powers security insights and analytics at scale? Do you want to contribute to the modernization of a security data platform that enables measurable improvements in application security across Amazon? As a Data Engineer on the AppStar DNA team (Data & Analytics Engineering), you will build and maintain data pipelines and infrastructure that support the AppStar organization. You will work across multiple data domains to develop the data infrastructure that powers analytics and reporting. You should be a builder who is passionate about data engineering and eager to learn. You thrive in solving technical problems, building reliable data pipelines, and contributing to a high-performing team. You bring solid expertise in data modeling, ETL/ELT pipeline design, and distributed data systems, and you're excited to grow your skills in modern data architectures and AWS technologies.

Source: Amazon.jobs

Original Article: https://amazon.jobs/en/jobs/10374267/data-engineer-appstar-data-analytics-engineering

More from the News Room

View all

We are publishing more related coverage here soon. Explore the full News Room for the latest articles.

See ROI in 12 weeks

See where enterprise data is slowing operations down.

Estimate the manual effort, delays, and leakage hidden across your current workflow before you automate it.