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Amazon
Amazon

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Data Engineer, Ring Agent Platforms

직무데이터 엔지니어링
경력미들급
위치Hawthorne, Canada, United States
근무오피스 출근
고용정규직
게시2주 전
지원하기

We are looking for a Data Engineer to design, build, and operate the data pipelines, models, and platform infrastructure that power Ring's analytics, science, and AI initiatives. You will 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.
You will use AI development IDEs and generative AI tooling daily to accelerate your work, and you will build multi-agent solutions that automate common data engineering tasks — pipeline generation, data quality enforcement, testing, and operational response. The goal is to turn repeatable patterns into agent-driven workflows that raise velocity and consistency across the team.
You will also contribute to the shared data platform when needed — improving developer tooling, maintaining infrastructure, and supporting the services that the broader data org depends on.

About the team
The Data and Agents Organization spans data engineering, business intelligence, applied science, and agentic AI. The org is structured into three primary groups: one focused on core data platforms, tooling, and pipeline infrastructure; another focused on AI/ML models, business analytics, shared data models, product analytics, and strategic science initiatives; and a third focused on building a multi-agent AI platform that enables teams to compose, deploy, and orchestrate autonomous AI agents at scale. Capacity is balanced across direct business support, strategic new development, and operational health.

Basic Qualifications

  • 3+ years of data engineering experience
  • Experience with data modeling, warehousing and building ETL pipelines
  • Experience with SQL
  • Experience with software development life cycle practices including code reviews, source control, CI/CD, testing, and operational support
  • Demonstrated use of generative AI tools (e.g., agentic coding assistants, AI-powered IDEs) in a professional or project setting

Preferred Qualifications

  • Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, Fire Hose, 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)

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants: Job duties for this position include: 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; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to 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. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, CA, Hawthorne - 132,100.00 - 178,800.00 USD annually

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Amazon 소개

Amazon

Amazon

Public

Amazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.

10,001+

직원 수

Seattle

본사 위치

$1.5T

기업 가치

리뷰

10개 리뷰

3.4

10개 리뷰

워라밸

2.5

보상

4.2

문화

3.0

커리어

3.8

경영진

2.7

65%

지인 추천률

장점

Great benefits and competitive pay

Learning and advancement opportunities

Good teamwork and colleagues

단점

High pressure and long hours

Poor work-life balance

Toxic work culture and management issues

연봉 정보

4개 데이터

L2

L6

L3

L4

L5

L2 · Data Analyst L2

0개 리포트

$108,330

총 연봉

기본급

$43,332

주식

$54,165

보너스

$10,833

$75,831

$140,829

면접 후기

후기 6개

난이도

4.0

/ 5

소요 기간

21-35주

경험

긍정 0%

보통 17%

부정 83%

면접 과정

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Technical Interview

6

Onsite/Virtual Interviews

자주 나오는 질문

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge