Data Engineer - BI Insights Group, Data Platform Department (DPD)

掲載中・2日前に確認

給与: 記載なし
勤務地: 東京都
休日: 記載なし
雇用形態: 記載なし

どんな仕事かAIによる生成

Design, develop, test, and implement scalable cloud-based data warehouse solutions, data pipelines, and data models. Manage and optimize data infrastructure and pipelines, ensure data quality, and build interactive reports and high-performance dashboards using data visualization tools.

応募資格・募集要項・仕事内容を見る

この求人に応募

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募集元で応募する楽天グループ株式会社の採用ページへ

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応募資格

必須

B.S. in Computer Science, or a related field, or equivalent education and experience
3+ years of end-to-end experience in data engineering (SQL) and operational experience in cloud-based or Linux systems
Experience in developing and building robust data warehouse ecosystems using Google Cloud Platform (GCP – BQ, GCS), Python, and shell scripting
Understanding of data warehouse/big data concepts, data modeling, batch-processing pipelines (ETL), and data integration techniques for managing large volumes of data
Hands-on experience creating and leveraging data visualization platforms (e.g., DOMO, Tableau, MicroStrategy, PowerBI, etc.)
Experience with Git

歓迎

Experience with Atlassian tools (Confluence, Jira, BitBucket)
Experience working on streaming data pipelines using tools such as Airflow, Apache Kafka, or Spark Streaming
Experience managing systems with high Service Level Objectives/Agreements (SLOs/SLAs)

求める人物像

Effective communication and project management skills
Quick learner, highly adaptable, and committed to continuous learning
Strong problem-solving and solution-creation mindset
Detail-oriented and driven by excellence
A "Can-Do" attitude and willingness to embrace new challenges
Strong teamwork and collaboration capabilities

募集要項最終確認 10/27

職種: データエンジニア
雇用形態: 記載なし
給与: 記載なし
勤務地: 東京都
働き方: 記載なし
経験年数: 3年以上
学歴: 大学卒業以上
掲載日: 2026/10/20 23:01（9日前）
最終確認: 2026/10/27 21:35（2日前）

仕事内容

Position Details

Hands-on design, development, testing, and implementation of scalable, cloud-based data warehouse solutions, optimized data pipelines, and robust data modeling
Maintain a healthy data warehouse ecosystem through comprehensive infrastructure management (system logs, storage, compute resources, batch scheduling, etc.), ensuring seamless data integration and proactively addressing performance bottlenecks
Internal Tooling: Adapt to and utilize Rakuten’s internal data pipeline orchestration framework, built on top of GCP-managed Airflow
Communication: Collaborate with cross-functional teams to identify data requirements and align them with business objectives
Documentation: Maintain comprehensive documentation, including platform architecture, data dictionaries, infrastructure configurations, operational processes and so on
Collaborate with Stakeholders: Work closely with end-users to understand requirements, gather feedback, and deliver impactful, customized reports
Solution Design: Propose and present visualization solutions to relevant stakeholders
Data Modeling & Mart Design: Architect reporting-specific data marts to ensure high-performance dashboards
Data Pipeline Management: Develop, maintain, and optimize pipelines, including DAG scheduling, data ingestion, and ETL/ELT processes to ensure data is "collected from" and "delivered to" efficiently and reliably
Data Quality Assurance: Validate and ensure the accuracy, consistency, and reliability of all data used in visualizations
Frontend Development: Design, build, and manage interactive reports using modern data visualization tools.

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