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Sr. Business Intel Engineer, Delivery Choices

Amazon

Sr. Business Intel Engineer, Delivery Choices

Amazon

Hyderabad, TS, IND

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Healthcare

401(k)

Equity

Parental Leave

Mental Health

Healthcare

401k

Equity

Parental Leave

Mental Health

Required Skills

SQL

Python

Data analysis

Statistical analysis

Machine learning

Data mining

At Amazon, Delivery Choices (DC), under Amazon's Delivery Experience (DEX) organization, is chartered to offer our Retail customers with alternatives to 'fast' delivery options by addressing their needs for control, choice, sustainability, and the convenience of receiving items together.

You will join a highly technical and entrepreneurial culture defining and building the next generation of software solution for the DC products and launching them in every Amazon store worldwide.

Are you customer obsessed, data oriented, technologically curious, and passionate about driving improvements to Amazon customer experiences? Amazon is seeking an experienced, talented, and motivated BIE Manager to join our team focused on driving new and improved customer experiences across Amazon's businesses globally.

Our DEX Delivery Choices (DC) team is seeking a skilled and motivated Senior Business Intelligence Engineer to analyze and deliver insights to help us better serve customers. The right candidate is passionate about understanding customer needs, perceptions, and experiences, diving deep into complex problems, and continuously striving to deliver deeper insights. The person in this role will innovate, build new methodologies to generate insights, and make recommendations to drive actions that directly impact our current and future customers. A successful candidate will possess excellent analytical skills, and have the ability to work collaboratively to influence business leaders at all levels, including senior management.

Basic Qualifications

  • 10+ years of professional or military experience
  • 5+ years of SQL experience
  • Experience programming to extract, transform and clean large (multi-TB) data sets
  • Experience with theory and practice of design of experiments and statistical analysis of results
  • Experience with AWS technologies
  • Experience in scripting for automation (e.g. Python) and advanced SQL skills.
  • Experience with theory and practice of information retrieval, data science, machine learning and data mining

Preferred Qualifications

  • Experience working directly with business stakeholders to translate between data and business needs
  • Experience managing, analyzing and communicating results to senior leadership

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

L2 · Data Analyst L2

0 reports

$108,330

total / year

Base

$43,332

Stock

$54,165

Bonus

$10,833

$75,831

$140,829

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