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Data Engineer, Amazon Business Data Analytics and Insights (ABDAI)

Amazon

Data Engineer, Amazon Business Data Analytics and Insights (ABDAI)

Amazon

Hyderabad, TS, IND

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Competitive salary and equity package

401(k) matching

Team events and activities

Professional development budget

Flexible work arrangements

Comprehensive health, dental, and vision insurance

Equity

Learning

Flexible Hours

Healthcare

Required Skills

Node.js

React

TypeScript

Amazon Business Data Analytics and Insights (ABDAI) team is looking for a Data Engineer (DE) to play a significant role in building their large-scale, high-volume, high-performance data integration and delivery services. These data solutions would be primarily used in periodic reporting, and drive business decision making while dealing efficiently with the massive scale of data available through our Data Warehouse as well as our software systems. You will be responsible for designing and implementing solutions using third-party and in-house reporting tools, modelling metadata, building reports and dashboards, and administering the platform software. You are expected to build efficient, flexible, extensible, and scalable data models, ETL designs and data integration services. You are required to support and manage growth of these data solutions.
You must be a self-starter and be able to learn on the go. Excellent written and verbal communication skills are required as you will work very closely with diverse teams.
As a Data Engineer in ABDAI team you will be working in one of the world's largest cloud-based data lakes. You should be skilled in the architecture of data warehouse solutions for the Enterprise using multiple platforms (EMR, RDBMS, Columnar, Cloud). You should have extensive experience in the design, creation, management, and business use of extremely large datasets. You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions, and to build data sets that answer those questions. Above all you should be passionate about working with huge data sets and someone who loves to bring datasets together to answer business questions and drive change.

Basic Qualifications

  • 3+ years of data engineering experience
  • 4+ years of SQL experience
  • Experience with data modeling, warehousing and building ETL pipelines

Preferred Qualifications

  • Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, Fire Hose, Lambda, and IAM roles and permissions
  • Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
    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