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트렌딩 기업

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채용Amazon

Manager III, Data Engineering, India Stores Tech

Amazon

Manager III, Data Engineering, India Stores Tech

Amazon

Bengaluru, KA, IND

·

On-site

·

Full-time

·

1mo ago

필수 스킬

Python

Java

SQL

AWS

Spark

Scala

Amazon India Stores Tech team is looking to hire a strong data engineering manager to build data & analytics platform for pan Amazon India businesses.

Amazon India Data Engineering & Analytics team is charted with democratizing data access for the entire marketplace & add productivity. That translates to owning the processing of every Amazon India transaction, for which the team is organized to have dedicated business owners & processes for each focus area. The DEM will play a key role in contributing to the success of each focus area, by partnering with respective business owners and leveraging data to identify areas of improvement & optimization. He / She will build deliverables like business process automation, payment behavior analysis, campaign analysis, fingertip metrics, failure prediction etc. that provide edge to business decision making AND can scale with growth. The role sits in the sweet spot between technology and business worlds AND provides opportunity for growth, high business impact and working with seasoned business leaders.

An ideal candidate will be someone with sound technical background in data domain – storage / processing / analytics, has solid business acumen and a strong automation / solution oriented thought process. Will be a self-starter who can start with a business problem and work backwards to conceive & devise best possible solution. Is a great communicator and at ease on partnering with business owners and other internal / external teams. Can explore newer technology options, if need be, and has a high sense of ownership over every deliverable by the team. Is constantly obsessed with customer delight & business impact / end result and ‘gets it done’ in business time.

Basic Qualifications

  • 5+ years of data engineering experience
  • Experience with data modeling, warehousing and building ETL pipelines
  • Experience with SQL
  • Experience managing a data or BI team
  • Experience leading and influencing the data or BI strategy of your team or organization
  • Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
  • Experience hiring, developing and promoting engineering talent

Preferred Qualifications

  • Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
  • Experience with AWS Tools and Technologies (Redshift, S3, EC2)

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.

총 조회수

1

총 지원 클릭 수

0

모의 지원자 수

0

스크랩

0

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