Business Intelligence Engineer

- 3+ years of SQL, ETL or Oracle experience
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience using Python scripting to process data for modeling
- Experience leveraging GenAI/LLM tools (e.g., Amazon Q, GitHub Copilot, Claude, ChatGPT) to improve productivity in data analysis, coding, or reporting workflows
- Business level Japanese both in verbal and written
- Business level English both in verbal and written
- Bachelor's degree or above in BI, finance, engineering, statistics, computer science, mathematics or equivalent quantitative field
- Experience working directly with business stakeholders to translate between data and business needs
- Experience designing and implementing GenAI-powered solutions (e.g., RAG-based applications, AI agents, automated insight generation, LLM-integrated data pipelines) that drive measurable business impact
- Experience leading GenAI/AI adoption initiatives within an organization, including use case identification, PoC development, guardrail design, and scaling best practices
- Experience with semantic layers, MCP (Model Context Protocol), or similar frameworks that enable AI agent access to structured data

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.
Amazonビジネスは、いつものAmazon（個人向けのAmazon.co.jp）に法人・個人事業主様向けの機能を追加した、ビジネス購買専門サービスです。個人向けのAmazon.co.jpの豊富な品揃えに加えビジネス向けの品揃えを拡充しています。また、法人価格や請求書払いなどの法人・個人事業主様のニーズに対応したサービスを提供しています。『地球上で最もお客様を大切にする企業であること』—これは世界で共通するAmazonの企業理念ですが、Amazonビジネスはまさに「お客様の声」から生まれました。Amazonビジネスは2015年4月に米国でスタートし、日本では2017年9月に始まりました。日本の法人・個人事業主様の購買の利便性を高めるため、当初から日本の商習慣に合わせた機能を提供しています。東証プライム市場に上場する企業の70%以上が登録しており、グローバルで連携を図りながら急速に成長を続けています。

Amazonでは、最新のAI Tool, 生成AIを日々の業務の中に積極的に取り入れています。
AI Toolは私たちの意思決定のスピードを加速させ、私たちを本当に重要な「判断」と「議論」に集中させることを可能にしています。Amazon では学習を継続する文化が根付いているため、ご自身のペースでAIに関する知識を深めることができるリソースが用意されています。

Amazon Business is a B2B procurement service that adds business-specific features to the familiar Amazon.co.jp experience. In addition to Amazon's vast consumer selection, it offers expanded business-relevant products, corporate pricing, Pay by Invoice, and other services tailored to the needs of businesses and sole proprietors. "To be Earth's most customer-centric company" — this is Amazon's global mission, and Amazon Business was born directly from customer feedback. Launched in the US in April 2015 and in Japan in September 2017, the service has been designed from the start to align with Japanese business customs. Over 70% of companies listed on the Tokyo Stock Exchange Prime Market are registered, and the business continues to grow rapidly with global collaboration across US, EU, and other regions.

At Amazon, you'll work alongside the latest AI and GenAI tools that are increasingly woven into how teams operate: from AI-powered capabilities that accelerate decision-making, to Generative AI that helps you focus on work that truly matters. You'll have opportunities and resources to develop AI fluency at your own pace, with continuous learning built into the culture.

Key job responsibilities
1) Stakeholderと連携したBI Solutionの設計と実行
- Sales・PM等のStakeholderと連携し、ビジネス課題を深く理解した上で最適なBI Solutionを設計・実装
- Self-serviceで活用可能なDashboard・Reportを設計・開発し、Dataに基づく意思決定を支援
- Engineering Excellence（正確性・効率性）とOperational Excellence（品質・信頼性）の基準を確立・維持
2) 大規模データの分析による戦略的洞察の提供
- 大規模データセットを統合・分析し、トレンドの発見や成長機会の特定
- 統計的手法やData Miningを用いて、複雑なビジネス課題に対する実用的な洞察を導出
- 分析結果をSenior Managementに対して明確に伝え、戦略的な意思決定とアクションを促進
3) GenAI・自動化を活用した生産性向上
- 反復的な手作業を特定し、Python等のスクリプトやGenAIを組み合わせた自動化ソリューションを設計・実装
- 新たな技術を評価・導入し、チーム全体の生産性と分析品質を継続的に改善

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1) Design and deliver BI solutions in partnership with stakeholders:
- Partner with stakeholders to deeply understand business challenges and design optimal BI solutions
- Design and develop self-service dashboards and reports that enable data-driven decision-making
- Establish and maintain standards for engineering excellence (correctness, efficiency) and operational excellence (quality, reliability)
2) Deliver strategic insights through large-scale data analysis:
- Integrate and analyze large-scale datasets to uncover trends and identify growth opportunities
- Apply statistical methods and data mining techniques to derive actionable insights for complex business problems
- Communicate findings clearly to senior management, driving strategic decisions and actions
3) Improve productivity through GenAI and automation:
- Identify repetitive manual tasks and design automation solutions combining scripting (Python) with GenAI capabilities
- Evaluate and adopt new technologies to continuously improve team productivity and analytical quality