One of our top clients a well-established Japanese company listed on the Tokyo Stock Exchange is currently looking for a Data Engineer to join their growing Data Center of Excellence (CoE) team.
Originally known for its strong foundation in consumer digital services the company has successfully expanded into high-impact domains such as Healthcare and Education (DX) driving real societal change through technology. With a stable business base and a strong focus on innovation they are now investing heavily in building scalable data platforms to support analytics machine learning and data-driven decision-making across the organization.
This is a great opportunity to work in a highly collaborative and international environment partnering closely with data scientists analysts and engineers to design and build reliable scalable data pipelines and modern data infrastructure.
You will play a key role in shaping the companys data architecture and contributing to a fast-growing high-impact data organization.
About the Role
We are looking for a Data Engineer responsible for building and operating data platforms that support analytics machine learning and cross-functional decision-making across the organization.
In this role you will collaborate closely with data scientists analysts and engineers to design and deliver reliable datasets and scalable data pipelines.
You will also be expected to contribute as a key member of a growing Data Center of Excellence (CoE) team.
Responsibilities
Data Architecture & Pipeline Development
Design build and operate data pipelines that enable reliable ingestion transformation and delivery of structured and semi-structured data
Ensure pipeline efficiency observability and maintainability including proper error handling and monitoring
Develop scalable ETL/ELT workflows to support analytics and product use cases
Data Integration & CoE Activities
Integrate data from multiple systems to create consistent well-structured and well-documented datasets
Contribute to standardized metric definitions common schemas and data consistency frameworks
Improve data discoverability and usability through documentation data dictionaries and data catalogs
Promote best practices in data governance and high-quality reproducible data operations
Analytics Support
Collaborate with data scientists and analysts to provide datasets optimized for analysis modeling and dashboarding
Understand stakeholder analytical needs and design data models that support exploration experimentation and performance analysis
Contribute to initiatives that improve data consistency accessibility and analytical efficiency
Requirements
Must-have Skills
Advanced SQL skills and experience with large-scale data warehouses (e.g. BigQuery Snowflake Redshift)
Experience building data pipelines data transformation and automation using languages such as Python
Experience with ETL/ELT frameworks orchestration tools and workflow scheduling
Strong understanding of data modeling (e.g. star schema normalization partitioning)
Ability to work autonomously validate assumptions propose improvements and drive technical solutions
Strong communication skills to collaborate with engineering and analytics teams
Preferred Skills
Experience with CI/CD version control and Infrastructure as Code
Knowledge of data quality frameworks validation techniques and metadata management
Experience contributing to Data CoE initiatives (e.g. semantic layers tracking infrastructure unified reporting systems)
Experience building data platforms to support LLM applications (e.g. preparing datasets for RAG evaluating model outputs building deployment pipelines)
Language Requirements
English: Ability to use English as the primary working language and independently participate in technical discussions and complex problem-solving with multinational teams (native level not required but high fluency expected)
Japanese: Business-level proficiency with the ability to communicate effectively with domestic stakeholders explain technical concepts clearly and facilitate smooth alignment
Benefits
Benefits Employment Type:
Full-time
Working Hours:
Flextime system (no core time)
Work Style:
Fully remote
Salary and Conditions:
Up to 7 million yen
Required Skills:
Must-have Skills Advanced SQL skills and experience with large-scale data warehouses (e.g. BigQuery Snowflake Redshift) Experience building data pipelines data transformation and automation using languages such as Python Experience with ETL/ELT frameworks orchestration tools and workflow scheduling Strong understanding of data modeling (e.g. star schema normalization partitioning) Ability to work autonomously validate assumptions propose improvements and drive technical solutions Strong communication skills to collaborate with engineering and analytics teams Preferred Skills Experience with CI/CD version control and Infrastructure as Code Knowledge of data quality frameworks validation techniques and metadata management Experience contributing to Data CoE initiatives (e.g. semantic layers tracking infrastructure unified reporting systems) Experience building data platforms to support LLM applications (e.g. preparing datasets for RAG evaluating model outputs building deployment pipelines) Language Requirements English: Ability to use English as the primary working language and independently participate in technical discussions and complex problem-solving with multinational teams (native level not required but high fluency expected) Japanese: Business-level proficiency with the ability to communicate effectively with domestic stakeholders explain technical concepts clearly and facilitate smooth alignment
One of our top clients a well-established Japanese company listed on the Tokyo Stock Exchange is currently looking for a Data Engineer to join their growing Data Center of Excellence (CoE) team.Originally known for its strong foundation in consumer digital services the company has successfully expan...
One of our top clients a well-established Japanese company listed on the Tokyo Stock Exchange is currently looking for a Data Engineer to join their growing Data Center of Excellence (CoE) team.
Originally known for its strong foundation in consumer digital services the company has successfully expanded into high-impact domains such as Healthcare and Education (DX) driving real societal change through technology. With a stable business base and a strong focus on innovation they are now investing heavily in building scalable data platforms to support analytics machine learning and data-driven decision-making across the organization.
This is a great opportunity to work in a highly collaborative and international environment partnering closely with data scientists analysts and engineers to design and build reliable scalable data pipelines and modern data infrastructure.
You will play a key role in shaping the companys data architecture and contributing to a fast-growing high-impact data organization.
About the Role
We are looking for a Data Engineer responsible for building and operating data platforms that support analytics machine learning and cross-functional decision-making across the organization.
In this role you will collaborate closely with data scientists analysts and engineers to design and deliver reliable datasets and scalable data pipelines.
You will also be expected to contribute as a key member of a growing Data Center of Excellence (CoE) team.
Responsibilities
Data Architecture & Pipeline Development
Design build and operate data pipelines that enable reliable ingestion transformation and delivery of structured and semi-structured data
Ensure pipeline efficiency observability and maintainability including proper error handling and monitoring
Develop scalable ETL/ELT workflows to support analytics and product use cases
Data Integration & CoE Activities
Integrate data from multiple systems to create consistent well-structured and well-documented datasets
Contribute to standardized metric definitions common schemas and data consistency frameworks
Improve data discoverability and usability through documentation data dictionaries and data catalogs
Promote best practices in data governance and high-quality reproducible data operations
Analytics Support
Collaborate with data scientists and analysts to provide datasets optimized for analysis modeling and dashboarding
Understand stakeholder analytical needs and design data models that support exploration experimentation and performance analysis
Contribute to initiatives that improve data consistency accessibility and analytical efficiency
Requirements
Must-have Skills
Advanced SQL skills and experience with large-scale data warehouses (e.g. BigQuery Snowflake Redshift)
Experience building data pipelines data transformation and automation using languages such as Python
Experience with ETL/ELT frameworks orchestration tools and workflow scheduling
Strong understanding of data modeling (e.g. star schema normalization partitioning)
Ability to work autonomously validate assumptions propose improvements and drive technical solutions
Strong communication skills to collaborate with engineering and analytics teams
Preferred Skills
Experience with CI/CD version control and Infrastructure as Code
Knowledge of data quality frameworks validation techniques and metadata management
Experience contributing to Data CoE initiatives (e.g. semantic layers tracking infrastructure unified reporting systems)
Experience building data platforms to support LLM applications (e.g. preparing datasets for RAG evaluating model outputs building deployment pipelines)
Language Requirements
English: Ability to use English as the primary working language and independently participate in technical discussions and complex problem-solving with multinational teams (native level not required but high fluency expected)
Japanese: Business-level proficiency with the ability to communicate effectively with domestic stakeholders explain technical concepts clearly and facilitate smooth alignment
Benefits
Benefits Employment Type:
Full-time
Working Hours:
Flextime system (no core time)
Work Style:
Fully remote
Salary and Conditions:
Up to 7 million yen
Required Skills:
Must-have Skills Advanced SQL skills and experience with large-scale data warehouses (e.g. BigQuery Snowflake Redshift) Experience building data pipelines data transformation and automation using languages such as Python Experience with ETL/ELT frameworks orchestration tools and workflow scheduling Strong understanding of data modeling (e.g. star schema normalization partitioning) Ability to work autonomously validate assumptions propose improvements and drive technical solutions Strong communication skills to collaborate with engineering and analytics teams Preferred Skills Experience with CI/CD version control and Infrastructure as Code Knowledge of data quality frameworks validation techniques and metadata management Experience contributing to Data CoE initiatives (e.g. semantic layers tracking infrastructure unified reporting systems) Experience building data platforms to support LLM applications (e.g. preparing datasets for RAG evaluating model outputs building deployment pipelines) Language Requirements English: Ability to use English as the primary working language and independently participate in technical discussions and complex problem-solving with multinational teams (native level not required but high fluency expected) Japanese: Business-level proficiency with the ability to communicate effectively with domestic stakeholders explain technical concepts clearly and facilitate smooth alignment
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