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Analytics Engineer (AI), Reverse Logistics (RL)

Amazon

Analytics Engineer (AI), Reverse Logistics (RL)

Amazon

Sunnyvale, CA, USA

·

On-site

·

Full-time

·

3w ago

필수 스킬

Python

AWS

Machine Learning

The Amazon Devices Reverse Logistics (ADRL) team seeks an Analytics Engineer specializing in AI-augmented analytics – You'll pioneer intelligent agentic systems by building multi-agent frameworks that enable natural language querying, automated insight generation, and intelligent workflow orchestration. You'll establish a curated, certified foundational data layer with robust governance, making Reverse Logistics data seamlessly accessible to AI tools and customers.

The ideal candidate combines expertise in generative AI, machine learning, and modern BI engineering—architecting solutions that unlock advanced analytical capabilities while maintaining enterprise-grade quality, security, and scalability.

  • Key job responsibilities

  • Build and evolve AI-driven analytics platform for ADRL organization – Develop intelligent systems using multi-agent frameworks that enable natural language querying, automated insight generation, and workflow orchestration to accelerate delivery, reduce manual effort, and scale BI solutions

  • Design and deploy agentic solutions for Reverse Logistics Business – Leverage Python and AWS services (Sage Maker, Bedrock, Lambda) to build intelligent automations for business workflows with real-time insights, delivering predictive recommendations, actionable insights, and proactive alerts to executive leadership

  • Curate foundational data layers and implement governance frameworks – Enable AI tools to leverage high-quality, semantically modeled data for business decision-making across ADRL

  • Partner with Data Engineering and Applied Science teams – Enhance data sources and analytics processes, explore AI/ML integration opportunities for more scalable and accurate reporting, and translate business requirements into scalable automated solutions

  • Create multi-agent frameworks serving as self-service hubs – Enable tailored querying and analytics access for all RL stakeholders across organizational data

  • Document patterns and establish guidelines for responsible AI use – Implement best practices for model monitoring, A/B testing, and continuous improvement

A day in the life
You leverage AI-powered tools like Amazon Quick Suite and Kiro to accelerate BI solution development through natural language queries and automated code generation. You build and maintain scalable ETL pipelines and semantic data models feeding traditional dashboards and AI-driven products while ensuring data quality through AI-assisted monitoring. You partner with Strategy, Product, and Data Engineering & Science stakeholders to translate business questions into structured solutions using rapid prototyping. You experiment with emerging AI/ML tools and agentic frameworks, evaluating capabilities like natural language querying, automated anomaly detection, and AI-assisted monitoring. You present findings through interactive dashboards and proof-of-concepts, communicating both value and limitations to technical and non-technical stakeholders.

About the team
The Amazon Devices Reverse Logistics (ADRL) team builds and sustains the global Amazon Device Reverse Supply Chain (RSC). ADRL processes ~7M returns annually, fulfills 1M warranty replacement requests from customers, and delivers 2M certified refurbished devices to pre-owned customers with an annual growth rate of 10%.

The RL BI (Analytics) team owns the data and reporting ecosystem for the RL business, delivering high-grade, certified data solutions that enable confident business decisions with superior data quality and integrity.

Basic Qualifications

  • 5+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
  • 3+ years of processing large, multi-dimensional datasets from multiple sources experience
  • Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
  • Experience in Statistical Analysis packages such as R, SAS and Matlab
  • Experience with data visualization using Tableau, Quicksight, or similar tools
  • Proficiency with AI tools and platforms – Building multi-agent systems using Tensor Flow, Py Torch, Lang Chain, and Auto Gen; integrating generative AI and LLMs; applying reinforcement learning and optimization algorithms
  • Experience with AWS DevOps/AI/ML services – Deploying and working with intelligent agentic RAG applications using Sage Maker, Bedrock, and Lambda

Preferred Qualifications

  • Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
  • Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
  • Experience with data modeling, warehousing and building ETL pipelines
  • Experience working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage

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, Sunnyvale - 114,500.00 - 185,000.00 USD annually

총 조회수

0

총 지원 클릭 수

0

모의 지원자 수

0

스크랩

0

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

2.9

10개 리뷰

워라밸

2.8

보상

3.7

문화

2.5

커리어

2.3

경영진

2.1

35%

친구에게 추천

장점

Good pay and compensation

Strong benefits package

Flexible scheduling options

단점

Poor management and leadership

Limited growth and promotion opportunities

High stress and demanding work environment

연봉 정보

4개 데이터

L2

L3

L4

L5

L6

L2 · Data Analyst L2

0개 리포트

$108,330

총 연봉

기본급

$43,332

주식

$54,165

보너스

$10,833

$75,831

$140,829

면접 경험

10개 면접

난이도

3.7

/ 5

소요 기간

21-35주

합격률

20%

경험

긍정 10%

보통 10%

부정 80%

면접 과정

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Loop

6

Team Matching

7

Offer

자주 나오는 질문

Coding/Algorithm

System Design

Behavioral/STAR

Leadership Principles

Technical Knowledge