We’re looking for a skilled and motivated Data Engineer to join our team. You’ll play a key role in building and maintaining our data infrastructure to ensure clean, reliable, and accessible data for analytics and business decision-making. If you’re passionate about working with data at scale, love solving complex problems, and enjoy cross-team collaboration — we’d love to hear from you!

What You’ll Do

Data Pipeline Development

• Build and maintain ETL pipelines to collect, clean, and transform data from multiple sources.
• Ensure data is accurate, complete, and ready for use.

Data Storage & Warehousing

• Manage and optimize databases, data warehouses, and data lakes.
• Structure data for easy access and efficient queries.

Data Modeling & Transformation

• Design data models and schemas that align with business needs.
• Prepare data for reporting and analysis.

Data Integration

• Work with teams across departments to bring data together from various systems.
• Apply data governance standards to maintain consistency and quality.

Performance Optimization

• Monitor and improve data pipeline performance and system reliability.
• Troubleshoot and resolve data-related issues.

Security & Compliance

• Apply security best practices to protect sensitive data.
• Ensure compliance with data protection regulations (e.g., GDPR, HIPAA).

Documentation & Knowledge Sharing

• Maintain clear documentation of pipelines, models, and architecture.
• Share best practices and support team learning.

Cross-functional Collaboration

• Partner with analysts, data scientists, and business teams to understand data needs.
• Coordinate with IT and DevOps to ensure smooth operations.

Who We’re Looking For

Must have

We’re looking for a detail-oriented Data Engineer who:

• Is fluent in English (both written and spoken).
• Has hands-on experience in data engineering, ETL development, and pipeline management.
• Is proficient in Python (or similar programming languages).
• Has strong SQL skills and database experience.
• Is familiar with tools like Google BigQuery, DataFusion, Airflow, etc.
• Understands GCP, Docker, Kubernetes, and cloud-based data architecture.
• Has a good understanding of data protection regulations and security best practices.
• Pays strong attention to detail and data quality at scale.

Nice to Have

• Understands which data is valuable to different teams and products.
• Familiarity with AI or experience in the logistics domain.

What We Offer

• 5-day work week with flexible working hours
• 2 remote workdays per week
• Lunch, gas, and coffee support
• Full social, health, and unemployment insurance + Health Insurance card
• 13th-month salary + performance bonus
• Annual salary review
• 12 annual leave days + 2 extra company holidays
• Team trips, team building, Happy Hour, and sports clubs (soccer, badminton, yoga, etc.)
• Learning opportunities with free courses (technical, soft skills, and English)
• Yearly health checkup
• Seniority-based benefits (e.g., PVI for family members)
• Technical & Japanese certification bonuses