Data Engineer【English Based Opportunity!】

Join a high-impact data engineering team building and optimizing scalable cloud-based data pipelines that power advanced analytics and data-driven decision-making. This role focuses on ETL development, data quality assurance, and leveraging modern technologies, including AI and data platforms such as GCP, BigQuery, Spark, and Databricks, to deliver reliable, high-quality insights for business growth.

Client Details

A global technology organization that leverages AI, data, and advanced analytics to drive innovation across multiple industries, including e-commerce, finance, and telecommunications. They are committed to transforming large-scale data into actionable insights through cutting-edge analytics platforms, enabling data-driven business growth and delivering impactful solutions for customers worldwide.

Description

• Design, build, and maintain scalable ETL/data pipelines on cloud platforms, ensuring optimal performance, reliability, and cost efficiency.
• Develop and implement data quality checks, validation processes, and monitoring frameworks to ensure accurate and timely delivery of analytics data.
• Collaborate with engineering, SRE, and customer-facing teams to troubleshoot issues, enhance data infrastructure, and support new feature development.
• Leverage modern technologies, including AI-powered tools and automation, to improve development workflows, optimize data processing, and drive continuous platform improvements.

Job Offer

• Competitive salary
• Office meals provided
• English based position in a global team

To apply online please click the 'Apply' button below. For a confidential discussion about this role please contact Serina Miyazono on +81 3 6627 6130.

• 5+ years of experience in data engineering, ETL pipeline development, or analytics platform engineering, preferably within cloud-based environments.
• Strong hands-on expertise with GCP, BigQuery, Spark, SQL, and Python, with experience building, maintaining, and troubleshooting large-scale data pipelines.
• Proven ability to collaborate effectively with cross-functional teams while demonstrating strong ownership, problem-solving skills, and a proactive mindset.
• Experience leveraging generative AI tools and automation technologies to improve development efficiency, data quality, and operational processes.