Junior Data Engineer

LIXIL makes pioneering water and housing products that make better homes a reality for everyone, everywhere. A better home is made up of surprisingly simple things – showers and faucets to experience water in new ways; kitchens that unleash creativity; toilets that provide cleanliness and comfort; doors and windows that connect you with the world outside; interiors and exteriors that bring spaces to life; baths to escape in after a long day.

Born in 2011 through a merger of five of Japan's most successful building materials and housing companies, we draw on our Japanese heritage to create world-leading technology and innovate to make high quality products that transform homes. Today, we're a global enterprise with approximately 53,000 employees in more than 150 countries worldwide, having expanded internationally by acquiring some of the most trusted names in our industry, including GROHE and American Standard.

1. Design & Develop Data Pipelines: Assist in building, maintaining, and optimizing scalable ETL/ELT data pipelines to ingest and transform large datasets from diverse sources, including APIs, databases, and third-party systems.
2. Data Modeling & Warehousing: Support the development of robust data models and schemas in both relational and cloud-native data warehouses (e.g., Google BigQuery).
3. Ensure Data Integrity: Monitor, troubleshoot, and improve the performance and reliability of data pipelines, ensuring data quality, consistency, and accuracy.
4. Data Source Integration: Work with various data formats and sources, including structured, semi-structured, and streaming data.
5. Data Governance & Security: Collaborate with senior engineers to enforce data governance, quality, and security standards across the organization.
6. Code & Automation: Write clean, efficient, and well-documented code (SQL, Python) for data engineering tasks. Utilize Git and CI/CD principles for version control and automated deployments.
7. Team Collaboration: Document data workflows and contribute to a shared knowledge base, providing ad-hoc support to data analysts and business users.

1. Educational Background: Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.
2. Professional Experience: 1-3 years of hands-on experience in a data engineering or similar role.
3. Technical Proficiency:
4. Communication & Soft Skills:
5. Availability: Able to join immediately.