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트렌딩 기업

트렌딩 기업

채용

채용Amazon

Data Engineer, Amazon Payment Products

Amazon

Data Engineer, Amazon Payment Products

Amazon

Bengaluru, KA, IND

·

On-site

·

Full-time

·

2w ago

Amazon Payment Products team creates and manages a global portfolio of products, including co-branded credit cards, installment financing, third party redemptions, and financial services marketplaces.
Within this team, we are looking for a Data Engineer (DE) to play a significant role in building 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, modeling 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 are passionate about working with huge datasets and have experience with the organization and curation of data for analytics. You have a strategic and long term view on architecting advanced data eco systems. 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.

Key job responsibilities
Implement data ingestion routines both real time and batch using best practices in data modeling, ETL/ELT processes by leveraging AWS technologies and big data tools.
Design, implement and operate large-scale, high-volume, high-performance data for analysis and data science.
Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture.
Collaborate with engineers/scientists to help adopt best practices in data system creation, data integrity, test design, analysis, validation, and documentation
Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service modeling and production support for customers.

Basic Qualifications

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

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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총 지원 클릭 수

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모의 지원자 수

0

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