Company Profile
With a strong commitment to digital transformation, it leverages data-driven strategies to enhance customer experiences, optimize operations, and drive innovation across its franchise network. Data engineers here play a key role in building scalable data infrastructure, enabling real-time analytics, and supporting business decisions that impact millions daily.
The Role
- Design & Build Scalable Data Infrastructure - Develop and optimize data pipelines, ensuring efficiency, security, and scalability.
- Define & Standardize Metrics - Collaborate with stakeholders to establish clear, actionable KPIs that align business and technical perspectives.
- Address Data Fragmentation - Integrate data from multiple systems to improve aggregation, visibility, and accessibility for analytics and decision-making.
- Ensure System Reliability - Maintain high system availability and performance while transitioning to real-time data processing.
- Lead the Shift to Real-Time Data - Migrate from batch processing to real-time data pipelines with minimal disruption to business operations.
Your Skills
- Proficient in real-time data pipeline development (Snowflake preferred, BigQuery, SQL Server)
- Experience in modern data architecture (Data Vault) and high-volume, low-latency ETL/ELT
- Proficient in SQL, Python, Git, YAML, JSON
- Japanese: Business Level is a must (primary) and English
Cloud & Data Platforms: Azure (preferred), GCP, or AWS; Knowledge of data catalog and data governance Process & Methodology - Experience with CI/CD pipelines and automation for scalability and reliability
- Familiar with Azure DevOps and Agile development
Location
Tokyo
Salary
9M JPY - 11M JPY
Selling points
- Unique Business Model: A "small big company"-massive in scale and brand recognition yet agile in operations. Easy cross-division communication enables direct collaboration with key decision-makers.
- High Impact Role: Influence business strategies by understanding how different divisions use data to drive decisions and optimize operations.
- Large-Scale Data: Work with vast and diverse data sets, offering exciting challenges in data engineering, optimization, and innovation.
- Manager coming from GAFAM
Reference Number: 06940-0013157821
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