채용
필수 스킬
Python
Java
Excel
Tableau
We are looking for a highly analytical Business Intelligence Engineer to join Amazon’s Global Accounting Business Intelligence and Analytics team.
The Accounting BI team supports the global Accounting organization with process automation/improvements, developing automated reporting solutions/tools, and improving the ability of the accounting organization to process, analyze, access and consume accurate and timely financial data. The team supports the global accounting organization and partners closely with accountants and financial analysts supporting the various businesses and industries Amazon operates in.
The ideal candidate thrives in a fast-paced environment, relishes working with ambiguity, big data, and enjoys the challenges of highly complex business context. This role requires an individual with excellent analytical abilities, deep knowledge of business intelligence solutions, and the ability to quickly learn, adapt and work with a variety of technologies.
Key job responsibilities
Key job responsibilities
Collaboration and partnership with Accounting and software development teams driving enterprise level projects
Contributing to the design, development, and maintenance of multiple scalable solutions supporting internal/external global stakeholders
Coordinating project prioritization with multiple stakeholders, managing and executing competing priorities from end to end within defined timelines
Supporting the global accounting organization with various ad-hoc reporting, analyses, and data processing needs
About the team
Who We Are:
The ATEAM (Accounting, Tools, Entities, Automation, and Management Reporting) Technology team is a dedicated group of program managers and technical resources in accounting who will identify manual effort reduction (MER) opportunities for operational accountants that includes the repetitive and mundane activities. In addition we help to facilitate process improvement workshops, document automation use cases, build, launch and manage the automations.
What We Do:
Identify manual effort reduction (MER) opportunities
Facilitate process improvement workshops
Document automation use cases
Build, launch, and manage automations
Basic Qualifications
- 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with one or more industry analytics visualization tools (e.g. Excel, Tableau, Quick Sight, MicroStrategy, PowerBI) and statistical methods (e.g. t-test, Chi-squared)
- Experience with scripting language (e.g., Python, Java, or R)
Preferred Qualifications
- Master's degree, or Advanced technical degree
- Knowledge of data modeling and data pipeline design
- Experience with statistical analysis, co-relation analysis
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
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스크랩
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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
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