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트렌딩 기업

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채용Amazon

Big Data Engineer, Chronicle

Amazon

Big Data Engineer, Chronicle

Amazon

Chennai, TN, IND

·

On-site

·

Full-time

·

1w ago

Impact
Ever wondered how Amazon offers the Earth's biggest selection and still manages to offer lower prices every day to our customers? Our retail business teams work with a massive array of vendors and business financial performance metrics to expand selection and drive costs lower. Given the rapid growth of our business, this requires our category leaders, financial analysts, site merchandisers and vendor managers to quickly analyze vendors, categories and brands, diving deep into data showing business efficiency down to the unit sale level. The technology that enables this has huge visibility and impact and is critical to Amazon's continued profitability and growth.

Innovation
We're working on the future. If you are seeking an environment where you can drive innovation. If you want to apply state-of-the-art software technologies to solve real world problems. If you want the satisfaction of providing visible benefit to end-users in an iterative fast paced environment, this is your opportunity. The responsibilities of this role will be key in paving the future of Amazon Retail and transforming how we do business.

Opportunity
You will be part of a team of creative, top-notch software developers to work hard, have fun, and make history. Software engineers at Amazon are more than just order takers; they see a problem and leverage innovative technology to address it. You will be working with very large data sets, well beyond the scalability limits of conventional relational databases. We're looking for people who innovate, love solving hard problems, and never take "no" for an answer.

Key job responsibilities

As part of our team, you will:

  • Design, implement, and support data warehouse/ data lake infrastructure using AWS bigdata stack, Python, Redshift, QuickSight, Glue/lake formation, EMR/Spark, Athena etc.
  • Creation and support of real-time data pipelines built on AWS technologies.
  • Incremental processing of data using Iceberg adn Spark
  • Collaborate with other Engineering teams, Product/ Managers/SDE's to implement AI based agentic analysis

Basic Qualifications

  • 3+ years of data engineering 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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모의 지원자 수

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스크랩

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Amazon 소개

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+

직원 수

Seattle

본사 위치

$1.5T

기업 가치

리뷰

2.9

10개 리뷰

워라밸

2.8

보상

3.7

문화

2.5

커리어

2.3

경영진

2.1

35%

친구에게 추천

장점

Good pay and compensation

Strong benefits package

Flexible scheduling options

단점

Poor management and leadership

Limited growth and promotion opportunities

High stress and demanding work environment

연봉 정보

4개 데이터

L2

L3

L4

L5

L6

L2 · Data Analyst L2

0개 리포트

$108,330

총 연봉

기본급

$43,332

주식

$54,165

보너스

$10,833

$75,831

$140,829

면접 경험

10개 면접

난이도

3.7

/ 5

소요 기간

21-35주

합격률

20%

경험

긍정 10%

보통 10%

부정 80%

면접 과정

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Loop

6

Team Matching

7

Offer

자주 나오는 질문

Coding/Algorithm

System Design

Behavioral/STAR

Leadership Principles

Technical Knowledge