Full RemoteBilingual Data Engineer
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Job Summary
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
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
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
