Data Engineer: AI-Driven Data Pipelines & Automation

Amazon; Seattle, Northern (WA, KY); On-site; USD 101,000 - 160,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon is seeking a Data Engineer to design, build, and operate data pipelines, models, and platform infrastructure powering Ring's analytics and AI initiatives. You will own the end-to-end data lifecycle— ingestion, transformation, modeling, quality enforcement, and delivery—ensuring reliable data for analysts, scientists, and AI systems at scale.

You will use AI development IDEs and generative AI tooling daily, building multi-agent solutions that automate data engineering tasks and raise

Qualifications

• 1+ years of data engineering experience.
• Experience with data modeling, warehousing and building ETL pipelines.
• Experience with SQL.
• Experience with one or more query languages (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala).
• Experience with one or more scripting languages (e.g., Python, KornShell).
• Experience with big data technologies such as Hadoop, Hive, Spark, EMR.
• Experience with ETL tools like Informatica, ODI, SSIS, BODI, Datastage, etc.

Responsibilities

• Design, build, and operate data pipelines, models, and platform infrastructure.
• Own end-to-end data lifecycle: ingestion, transformation, modeling, quality enforcement, delivery.
• Build multi-agent solutions that automate data engineering tasks and improve velocity and consistency.
• Contribute to shared data platform, tooling, and infrastructure to support broader data org.

Skills

Data modeling

SQL

Data warehousing

ETL pipelines

Python

Scripting

Tools

Hadoop

Hive

Spark

EMR

Informatica

Job description

Amazon is seeking a Data Engineer to design, build, and operate data pipelines, models, and platform infrastructure powering Ring's analytics and AI initiatives. You will own the end-to-end data lifecycle— ingestion, transformation, modeling, quality enforcement, and delivery—ensuring reliable data for analysts, scientists, and AI systems at scale.

You will use AI development IDEs and generative AI tooling daily, building multi-agent solutions that automate data engineering tasks and raise