Job Description

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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