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 design, modernize, and optimize large-scale cloud data platforms that support advanced analytics, AI initiatives, and business intelligence.
As demand for enterprise data modernization continues to grow, the company is expanding its Data Engineering practice to deliver next-generation cloud data architectures, scalable analytics platforms, and AI-ready data ecosystems using leading cloud technologies and modern data platforms.
Job Role
The Senior Data Engineer will serve as a technical leader responsible for designing, building, and optimizing enterprise-scale cloud data platforms. Working closely with solution architects, data scientists, cloud engineers, and project stakeholders, this role will lead the development of scalable data infrastructure that enables advanced analytics, machine learning, and AI-driven business solutions.
The position offers the opportunity to lead cloud migration initiatives, evaluate emerging technologies, and mentor engineering teams while helping enterprise clients accelerate their digital transformation journey.
Key Responsibilities
Design and implement scalable cloud-based data platforms using AWS, Microsoft Azure, Google Cloud Platform (GCP), Databricks, and Snowflake.
Lead enterprise data platform architecture, data warehouse (DWH), and data lake implementation projects.
Design, develop, and optimize large-scale distributed data processing pipelines using Spark, Python, and modern ETL frameworks.
Lead cloud migration initiatives from on-premises environments to cloud-native data platforms.
Evaluate emerging technologies, conduct Proof of Concept (PoC) activities, and recommend optimal technical solutions.
Develop and maintain robust data models that support analytics, business intelligence, and AI workloads.
Collaborate with cross-functional teams to ensure data quality, security, governance, and platform reliability.
Mentor junior engineers and provide technical leadership throughout the project lifecycle.
Candidate Requirements
Bachelor's degree or above in Computer Science, Information Technology, Software Engineering, Data Engineering, or a related discipline.
Minimum 3 years of practical experience in Data Engineering or related fields.
Proven experience designing and building cloud-based data infrastructure using AWS, Microsoft Azure, or Google Cloud Platform (GCP).
Strong experience developing large-scale distributed data processing pipelines using Spark and Python.
Solid understanding of data modeling, ETL development, and enterprise data architecture.
Experience with Databricks or Snowflake is highly preferred.
Knowledge of data governance, data quality, metadata management, and cloud security best practices is an advantage.
Cloud certifications (AWS, Azure, GCP, Snowflake, or Databricks) are highly desirable.
Experience using AI or Generative AI to improve software development or engineering workflows is a plus.
Strong analytical thinking, technical leadership, and problem-solving capabilities.
Professional English communication skills are preferred.
Candidates eligible for relocation and visa sponsorship are encouraged to apply.