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Data Engineer II, ISS

Amazon

Data Engineer II, ISS

Amazon

Hyderabad, TS, IND

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Healthcare

401(k)

Equity

Healthcare

401k

Equity

Required Skills

Data Engineering

SQL

Data Modeling

ETL

Data Warehousing

Join us in the International Seller Services Central Analytics Team and Tackle Data Warehousing and Reporting Challenges!

We are a dedicated group of BIE, DE, DS, AS and BAs within the Seller Services organization at Amazon. Our mission is to deliver data-driven analytical solutions that empower sellers to thrive on Amazon's global platform. We specialize in constructing and maintaining intricate standard data pipelines that are used by thousands of users across the globe to measure, derive and analyze performance of the sellers selling on Amazon.

We are currently in search of a brilliant, self-driven, and seasoned DE II to join our team. In this role, you will have the opportunity to work on building scalable solutions, including extensive data models and complex ETL pipelines and utilize your expertise to raise the bar on data timeliness, discoverability and availability of the same.

  • Key job responsibilities
  • Design and implement scalable, secure data pipelines and infrastructure using AWS technologies and big data tools
  • Build and maintain high-performance ETL processes that handle large-scale, complex datasets
  • Architect end-to-end analytical solutions that are highly available, stable, and cost-effective
  • Transform raw data into actionable insights through effective data modeling and integration
  • Implement best practices in data system creation, data integrity, and documentation
  • Proactively identify opportunities for process improvement and automation
  • Partner with business stakeholders to gather requirements and translate them into technical solutions

Basic Qualifications

  • 3+ years of data engineering experience
  • 4+ years of SQL experience
  • Experience with data modeling, warehousing and building ETL pipelines
  • 3+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience

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