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Business Intelligence Engineer, Search Capacity

Amazon

Business Intelligence Engineer, Search Capacity

Amazon

Tokyo, 13, JPN

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Comprehensive health, dental, and vision insurance

Competitive salary and equity package

Professional development budget

Team events and activities

Flexible work arrangements

401(k) matching

Healthcare

Equity

Learning

Flexible Hours

Required Skills

React

PostgreSQL

TypeScript

The Amazon Search team creates customer-focused search solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, Amazon Search service go to work. We design, develop, and deploy high performance, fault-tolerant, distributed search systems used by millions of Amazon customers every day.
As a Business Intelligence Engineer in the Search Capacity team, you will:

  • Scale the Amazon Search service by working closely with service owners in engineering and operations to understand the service in depth and drive optimal scaling and capacity planning.
  • Identify and track key performance metrics around efficiency and costs.
  • Manage planning, ordering, and budgeting for hardware and other computational resources.
  • Develop and improve tools for automating the foregoing responsibilities wherever possible.
  • Analyze resource utilization and performance test data to identify variables impacting performance and scalability. Develop models for required hardware resources to meet current and future SLAs.

Basic Qualifications

  • Bachelor's degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field
  • Experience with forecasting and statistical analysis
  • Experience with data visualization using Tableau, Quicksight, or similar tools
  • Experience with data modeling, warehousing and building ETL pipelines
  • 3+ years of data engineering, database engineering, business intelligence or business analytics experience
  • Experience in scripting for automation (e.g. Python) and advanced SQL skills.

Preferred Qualifications

  • Master's degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field
  • Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
  • Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business
    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.

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About 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+

Employees

Seattle

Headquarters

Reviews

2.9

10 reviews

Work Life Balance

2.8

Compensation

3.7

Culture

2.5

Career

2.3

Management

2.1

35%

Recommend to a Friend

Pros

Good pay and compensation

Strong benefits package

Flexible scheduling options

Cons

Poor management and leadership

Limited growth and promotion opportunities

High stress and demanding work environment

Salary Ranges

2 data points

L2

L3

L4

L5

L6

M3

M4

M5

M6

L2 · Product Designer L2

0 reports

$163,720

total / year

Base

$65,488

Stock

$81,860

Bonus

$16,372

$114,604

$212,836

Interview Experience

10 interviews

Difficulty

3.7

/ 5

Duration

21-35 weeks

Offer Rate

20%

Experience

Positive 10%

Neutral 10%

Negative 80%

Interview Process

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Loop

6

Team Matching

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Leadership Principles

Technical Knowledge