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Business Intel Engineer I, Japan Central Ops
필수 스킬
Excel
セントラルオペレーション(CO)は、Amazon Logistics のチームであり、ますます複雑化し拡大するラストマイル配送ネットワークの運用において、スケーラブルなソリューションを提供するため、新たなアプローチと働き方を追求しています。COは、ルート計画、スケジュール管理と予測、オンロード管理など、ラストマイル配送における重要なプロセスを担当し、これらのプロセスをスケーラブルな方法で継続的に変革していくというビジョンを持っています。
私たちは、チームに加わり、セントラルオペレーション(CO)内で使用されるプロセスとテクノロジーの改善を推進するビジネスインテリジェンスエンジニアを探しています。この候補者は、新しく、しばしば曖昧なチームにおいて、卓越した能力を発揮し、成長できる必要があります。採用された候補者は、大きな視点で考え、独創的なアイデアを生み出し、輸送チーム、ラストマイル技術チーム、オペレーション、ビジネス開発チームに直接影響を与え、協力することで、COのさらなる拡大に向けた戦略的アプローチを策定する責任を負います。
Central Operations (CO) is a team at Amazon Logistics that pursues new approaches and ways of working to provide scalable solutions for running our increasingly complex and growing last-mile delivery network. The CO is responsible for critical processes in the last mile of delivery, including route planning, scheduling and forecasting, and on-road management, with a vision to continuously transform how we do this in a scalable way.
We are looking for a Business Intel Engineer to join the team and drive improvements to the processes and technology used within Central Operations (CO). This candidate must have the ability to excel and thrive in a new, often ambiguous team. The successful candidate will be responsible for thinking big, developing original ideas, and directly influencing and collaborating with the Transportation Team, Last Mile Tech Team, Operations, and Business Development Team to develop a strategic approach to further expand CO.
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Key job responsibilities
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プログラム (ミッション、ビジョン、理念) を定義し、目標を設定し、データを分析し、指標で定量化された改善を推進します
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ビジネス上の問題、自動化の限界、Scaling Factorとテクノロジーの限界、およびリーダーの意思決定の背景を理解しプログラムを推進する
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複数のプロジェクトとタスクを同時に管理し、社内のビジネス パートナーに影響を与え、交渉し、コミュニケーションを取る
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チーム、プロセス、システム間のギャップを監督する
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ビジネスリスクを特定して軽減する (障害となる前に)
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クリティカル パスのスケジュールが確実に守られ、リソースのニーズが理解され、プロジェクトの優先順位がSenior Managementに見えるようにする
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運用、製品チーム、エンジニアリング チームと緊密に連携して根本原因を特定し、システムの機能と信頼性の向上に関連する複雑な問題を解決します
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計画と分析において他のアナリストや BI エンジニアと協力して、ビジネス目標を達成するための分析ソリューションを構築する
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Define the program (mission, vision, tenets), set objectives, analyze data, and drive improvements that are quantified with metrics
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Seek to understand business problems, automation limitations, scaling factors, boundary conditions and reasons behind leadership decisions
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Manage multiple projects and tasks simultaneously and influence, negotiate, and communicate with internal business partners
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Oversee gaps between teams, processes and systems
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Identify and mitigate risks (before they become roadblocks)
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Ensure critical path timelines are met, resource needs are understood and project prioritization is visible to senior leadership
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Work closely with operations, product teams and engineering teams to root cause and solve complex problems related to increasing capability and reliability of our systems
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Partnering with other analysts and BI engineers in planning and analytics to build analytical solutions to deliver on business goals
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A day in the life
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Collaborate with a diverse range of stakeholders, both technical and non-technical, to provide comprehensive BI solutions.
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Develop and refine a robust data architecture and reporting framework by navigating various business criteria to ensure data accuracy and reliability.
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Own creating, evolving, and managing essential metrics, reports, analyses, and dashboards that drive key business decisions.
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Uphold high standards in reporting and analytical practices, focusing on data accuracy, experimental design, methodologies, validation processes, and thorough documentation.
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Build knowledge regarding advancements in technology, tools, methodologies, and best practices in analytics, and disseminate this knowledge within the team.
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Extract valuable insights from client feedback and operational data, propose actionable recommendations, and support GO-AI leadership in making pivotal business decisions.
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Design and execute studies to assess the impact and efficiency of various initiatives, supporting the improvement of key performance indicators and influencing the strategic direction in the long term.
Basic Qualifications
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, Fire Hose, Lambda, and IAM roles and permissions
- Experience in Business English skills, both verbal and written
- Interested in working with diverse team members and contributing to an inclusive culture
Preferred Qualifications
- Master's degree
- Speak, write, and read fluently in Japanese
- Experience gathering business requirements, using industry standard business intelligence tool(s) to extract data, formulate metrics and build reports
- Experience building and maintaining basic data artifacts (e.g., ETL, data models, queries)
- Knowledge of data modeling and data pipeline design
- Knowledge of how to improve code quality and optimizes BI processes (e.g. speed, cost, reliability)
- Comfort with ambiguity and eagerness to learn new skills.
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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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
10개 리뷰
3.4
10개 리뷰
워라밸
2.5
보상
4.2
문화
3.0
커리어
3.8
경영진
2.7
65%
지인 추천률
장점
Great benefits and competitive pay
Learning and advancement opportunities
Good teamwork and colleagues
단점
High pressure and long hours
Poor work-life balance
Toxic work culture and management issues
연봉 정보
4개 데이터
L2
L6
L3
L4
L5
L2 · Data Analyst L2
0개 리포트
$108,330
총 연봉
기본급
$43,332
주식
$54,165
보너스
$10,833
$75,831
$140,829
면접 후기
후기 6개
난이도
4.0
/ 5
소요 기간
21-35주
경험
긍정 0%
보통 17%
부정 83%
면접 과정
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Technical Interview
6
Onsite/Virtual Interviews
자주 나오는 질문
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
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