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职位Amazon

Business Intelligence Engineer II, Product & E-commerce Analytics

Amazon

Business Intelligence Engineer II, Product & E-commerce Analytics

Amazon

Austin, TX, USA

·

On-site

·

Full-time

·

1mo ago

必备技能

Python

SQL

AWS

Tableau

We are seeking a Business Intelligence Engineer II to join the Product & E-commerce Analytics team supporting Whole Foods Market's digital presence. This role will provide insights into our digital products (Whole Foods Market on Amazon, Whole Foods Market web, and the Whole Foods Market app), the in-store and online checkout experience, foundational data quality, and new technical product initiatives. You'll deliver data-driven insights and analytics solutions across the product development lifecycle, partnering with Product and E-commerce teams to drive decision-making through data analysis, reporting, and insights generation.

Key job responsibilities

  • Analytics Development & Insights

  • Establish and track engagement metrics for digital products and e-commerce platforms

  • Analyze and extract relevant information from large and complicated data sets of structured and unstructured data to identify insights that influence business decisions and product roadmaps

  • Develop deep knowledge of a variety of data sources, including customer, transaction, marketing, inventory, and digital data

  • Technical Execution & Automation

  • Design, develop, and maintain scaled, automated, and user-friendly systems, reports, and dashboards using Quick Sight or similar tools

  • Collaborate with product and technical teams to consult, develop, and track KPIs and automate reporting/process solutions

  • Perform data infrastructure improvements to meet team needs

  • Design and implement data models and ETL/ELT processes using AWS services including S3 and Redshift

  • Optimize performance and usability of analytics products with expert-level SQL skills

  • Ensure data quality, integrity, and consistency across analytical outputs

  • Product Development Support

  • Support product teams throughout the development lifecycle to define success metrics and measurement approaches

  • Implement measurement frameworks for new products and features

  • Lead requirements gathering sessions with product teams and business stakeholders

  • Maintain analytics documentation and knowledge base for product initiatives

  • Collaboration & Communication

  • Translate complex analytical findings into actionable business recommendations for stakeholders and senior management

  • Partner with cross-functional teams including Product Management, E-commerce, Operations, Marketing Analytics, and Technology

  • Lead projects independently with minimal supervision

Basic Qualifications

  • Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
  • 3+ years of developing automated reporting experience
  • 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
  • 1+ years of processing large, multi-dimensional datasets from multiple sources experience
  • 1+ years of performing statistical analysis experience
  • Experience with data visualization using Tableau, Quicksight, or similar tools
  • Experience with data modeling, warehousing and building ETL pipelines
  • Bachelor's degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field

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 working as a BIE in a technology company
  • Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business
  • Master's degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field

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

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, TX, Austin - 99,500.00 - 160,000.00 USD annually

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关于Amazon

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+

员工数

Seattle

总部位置

$1.5T

企业估值

评价

2.9

10条评价

工作生活平衡

2.8

薪酬

3.7

企业文化

2.5

职业发展

2.3

管理层

2.1

35%

推荐给朋友

优点

Good pay and compensation

Strong benefits package

Flexible scheduling options

缺点

Poor management and leadership

Limited growth and promotion opportunities

High stress and demanding work environment

薪资范围

4个数据点

L2

L3

L4

L5

L6

L2 · Data Analyst L2

0份报告

$108,330

年薪总额

基本工资

$43,332

股票

$54,165

奖金

$10,833

$75,831

$140,829

面试经验

10次面试

难度

3.7

/ 5

时长

21-35周

录用率

20%

体验

正面 10%

中性 10%

负面 80%

面试流程

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Loop

6

Team Matching

7

Offer

常见问题

Coding/Algorithm

System Design

Behavioral/STAR

Leadership Principles

Technical Knowledge