Data Engineer, Ring Agent Platforms

Amazon is seeking a Data Engineer to support Ring's analytics, science, and AI initiatives. The role designs, builds, and operates scalable data pipelines, models, and platform infrastructure; manages the end-to-end data lifecycle; and develops AI-driven workflows to automate data engineering tasks. The position also contributes to shared data platforms, developer tooling, infrastructure, and operational services.

Responsibilities

Design, build, and operate the data pipelines, models, and platform infrastructure that power Ring's analytics, science, and AI initiatives

Own the end-to-end data lifecycle — ingestion, transformation, modeling, quality enforcement, and delivery — ensuring that analysts, scientists, and AI systems have access to reliable, well-structured data at scale

Use AI development IDEs and generative AI tooling daily to accelerate your work, and build multi-agent solutions that automate common data engineering tasks — pipeline generation, data quality enforcement, testing, and operational response

Turn repeatable patterns into agent-driven workflows that raise velocity and consistency across the team

Contribute to the shared data platform when needed — improving developer tooling, maintaining infrastructure, and supporting the services that the broader data org depends on

Work safely and cooperatively with other employees, supervisors, and staff

Adhere to standards of excellence despite stressful conditions

Communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service

Follow all federal, state, and local laws and Company policies

Exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation

Preferred

Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions

Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)

Experience designing or building AI agents or multi-agent solutions that automate engineering workflows

Familiarity with agentic AI patterns including tool use, function calling, and multi-agent orchestration

Familiarity with at least one agentic AI development IDE

Experience building or maintaining shared data models, semantic layers, or data contracts

Familiarity with data governance, cataloging, or lineage tracking

Experience contributing to shared platform infrastructure, developer tooling, or self-service data services

Familiarity with observability tooling for data pipelines (logging, metrics, alerting)

AWS technologies

Redshift

S3

AWS Glue

EMR

Kinesis

FireHose

Lambda

IAM roles

non-relational databases

object storage

document stores

key-value stores

graph databases

column-family databases

AI agents

multi-agent solutions

agentic AI patterns

function calling

multi-agent orchestration

AI development IDE

shared data models

semantic layers

data contracts

data governance

cataloging

lineage tracking

platform infrastructure

developer tooling

self-service data services

observability tooling

data pipelines

logging

metrics

alerting

Benefits

Sign-on payments

Restricted stock units (RSUs)

Health insurance

Medical insurance

Dental insurance

Vision insurance

Prescription coverage

Basic Life & AD&D insurance

Option for Supplemental life plans

Employee Assistance Program (EAP)

Mental Health Support

Medical Advice Line

Flexible Spending Accounts

Adoption and Surrogacy Reimbursement coverage

401(k) matching

Paid time off

Parental leave

Company

Online retail and cloud computing services

Seattle, Washington, USA

https://amazon.com/

Founded in 1994

10001+ employees

Qualifications

3+ years of data engineering experience

Experience with data modeling, warehousing and building ETL pipelines

Experience with SQL

Experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations

Demonstrated use of generative AI tools (e.g., agentic coding assistants, AI-powered IDEs) in a professional or project setting

Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions

Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)

Experience designing or building AI agents or multi-agent solutions that automate engineering workflows

Familiarity with agentic AI patterns including tool use, function calling, and multi-agent orchestration

Familiarity with at least one agentic AI development IDE

Experience building or maintaining shared data models, semantic layers, or data contracts

Familiarity with data governance, cataloging, or lineage tracking

Experience contributing to shared platform infrastructure, developer tooling, or self-service data services

Familiarity with observability tooling for data pipelines (logging, metrics, alerting)

Required skills

Data Engineering, Data Modeling, Data Warehousing, ETL Pipelines, SQL, Software Development Lifecycle, Generative AI Tools, AWS Redshift, Amazon S3, AWS Glue, Amazon EMR, Amazon Kinesis, Amazon Kinesis Data Firehose, AWS Lambda, AWS IAM, Non-relational Databases, AI Agents, Multi-agent Orchestration

Preferred skills

Familiarity with at least one agentic AI development IDE

Experience

3+ years