채용
필수 스킬
SQL
AWS
Spark
About the Organization: Amazon is a US-based multinational electronic commerce company headquartered in Seattle, Washington. Amazon.com started as an online bookstore, but soon diversified into many other categories, with a vision to be earth's most customer-centric company & to build a place where people can come to find and discover anything they might want to buy online.
About the role: Amazon's Global Finance Services (GFS) team is a fast-paced, team-focused, dynamic environment and delivering great experiences for our customers is top priority. GFS is seeking a Business Intelligence Engineer to support our Amazon Music finance team.
As a Data Engineer, You will be working on building and maintaining complex data pipelines, assemble large and complex datasets to generate business insights and to enable data driven decision making and support the rapidly growing and dynamic business demand for data.
You will have an opportunity to collaborate and work with various teams of Business analysts, Managers, Business Intelligence, and Data Engineers to determine how best to design, implement and support solutions. You will be challenged and provided with tremendous growth opportunity in a customer facing, fast paced, agile environment.
- Key job responsibilities
- Design, implement and support an analytical data platform solutions for data driven decisions and insights
- Design data schema and operate internal data warehouses & SQL/NOSQL database systems
- Work on different data model designs, architecture, implementation, discussions and optimizations
- Interface with other teams to extract, transform, and load data from a wide variety of data sources using AWS big data technologies like EMR, Red Shift, Elastic Search etc.
- Work on different AWS technologies such as S3, Red Shift, Lambda, Glue, etc.. and Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency
- Work on data lake platform and different components in the data lake such as Hadoop, Amazon S3 etc.
- Work on SQL technologies on Hadoop such as Spark, Hive, Impala etc..
- Help continually improve ongoing analysis processes, optimizing or simplifying self-service support for customers
- Must possess strong verbal and written communication skills, be self-driven, and deliver high quality results in a fast-paced environment.
- Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation.
- Enjoy working closely with your peers in a group of talented engineers and gain knowledge.
- Be enthusiastic about building deep domain knowledge on various Amazon’s business domains.
- Own the development and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions.
Basic Qualifications
- 1+ years of data engineering experience
- Experience with SQL
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
- Experience with one or more scripting language (e.g., Python, Korn Shell)
Preferred Qualifications
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.
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
0
총 지원 클릭 수
0
모의 지원자 수
0
스크랩
0
비슷한 채용공고
Amazon 소개

Amazon
PublicAmazon.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
뉴스 & 버즈
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