Junior Data Engineer (Cloud Data Platform & ETL)
Confirmed on the employer's own hiring board on Oct 13, 2026. First seen by Alion on Oct 13, 2026.
This role requires the candidate to work on-site in Tokyo, Japan.
Client Overview
Our client is a global technology solutions provider specializing in Artificial Intelligence (AI), Cloud Computing, Data Engineering, and Digital Transformation (DX). The organization partners with enterprise clients across multiple industries to build modern cloud data platforms, scalable analytics infrastructure, and AI-ready data ecosystems that support business growth and innovation.
As demand for cloud-native data solutions continues to increase, the company is expanding its Data Engineering team to develop the next generation of data platforms while providing engineers with opportunities to work alongside experienced technical specialists using leading cloud and big data technologies.
Job Role
The Junior Data Engineer will support the development, implementation, and maintenance of cloud-based data platforms and data pipelines. Working under the guidance of senior engineers, this role will contribute to ETL/ELT development, cloud data migration, infrastructure implementation, and technical documentation while building hands-on experience with modern data engineering technologies.
This position offers an excellent opportunity for early-career engineers who are passionate about cloud computing, big data, and data engineering to accelerate their technical growth in a collaborative environment.
Key Responsibilities
Support the development, maintenance, and monitoring of cloud-based ETL/ELT data pipelines.
Assist in migrating on-premises data warehouses to modern cloud data platforms and data lakehouse environments.
Participate in the implementation and configuration of cloud-based data infrastructure using modern data engineering tools.
Develop and maintain SQL queries, data transformation logic, and data processing workflows.
Collaborate with senior engineers to troubleshoot technical issues and improve data platform performance.
Prepare and maintain technical documentation, design specifications, operational manuals, and implementation guides.
Support testing, deployment, and operational monitoring of enterprise data solutions.
Continuously learn and apply emerging technologies in cloud computing, big data, and AI-driven data engineering.
Candidate Requirements
Bachelor's degree in Computer Science, Information Technology, Software Engineering, Data Engineering, or a related discipline.
Minimum 1 year of practical experience using SQL for data extraction, transformation, and analysis.
Experience programming with Python, Java, or Scala.
Basic understanding of Relational Database Management Systems (RDBMS).
Familiarity with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP) is preferred.
Basic knowledge of Data Warehouses (DWH), Data Lakes, ETL/ELT processes, or modern data platforms is an advantage.
Experience with Git, Linux, Shell scripting, Databricks, or Snowflake is highly desirable.
Strong willingness to learn cloud computing, big data technologies, and modern data engineering practices.
Interest in AI, Generative AI, and emerging technologies that improve software engineering and data workflows.
Strong analytical thinking, teamwork, communication, and problem-solving skills.
Professional English communication skills are preferred.
Candidates eligible for relocation and visa sponsorship are encouraged to apply.