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Business Intelligence Engineer II, AOP

Amazon

Business Intelligence Engineer II, AOP

Amazon

Bengaluru, KA, IND

·

On-site

·

Full-time

·

2w ago

Benefits & Perks

Healthcare

401(k)

Parental Leave

Healthcare

401k

Parental Leave

Required Skills

SQL

Python

Tableau

Quicksight

Data Modeling

ETL

R

SAS

Matlab

Statistical Analysis

  • Amazon strives to be Earth's most customer-centric company where people can find and discover virtually anything they want to buy online. By giving customers more of what they want - low prices, vast selection, and convenience
  • Amazon continues to grow and evolve as a world-class e-commerce platform. The AOP team is an integral part of this and strives to provide Analytical Capabilities to fulfil all customer processes in the IN-ECCF regions.
    The Business intelligence engineer would support the analytical requirements of the IN-ECCF Operations Analytics team. Candidate will be responsible for conducting deep dive analyses to solve complex business problems. He/ she will also be responsible for creating robust/automated reporting frameworks to increase visibility into data and enable data driven decision making. Another key aspect of the job is to unearth insights from data to help the operations team in driving process excellence. This position requires excellent statistical knowledge, superior analytical abilities, good knowledge of business intelligence solutions and exposure to efficient data engineering practices. The BIE will also be a good stakeholder manager as he/she will have to work closely with Ops stakeholders. Candidate should be comfortable with ambiguity, capable of working in a fast-paced environment, continuously improving technical skills to meet business needs, possess strong attention to detail and be able to collaborate with customers to understand and transform business problems into requirements and deliverables.

Basic Qualifications

  • 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
  • Experience with data visualization using Tableau, Quicksight, or similar tools
  • Experience with data modeling, warehousing and building ETL pipelines
  • Experience in Statistical Analysis packages such as R, SAS and Matlab
  • Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling

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

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