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
Integrate data from multiple systems to create consistent, well-structured, and well-documented datasets
Collaborate with data scientists and analysts to provide datasets optimized for analysis, modeling, and dashboarding
Contribute to initiatives that improve data consistency, accessibility, and analytical efficiency.

Requirements

3 Years + experience in System & Software Engineering
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
English: Ability to use English as the primary working language and independently participate in technical discussions and complex problem-solving with multinational teams
Japanese: Business-level proficiency, with the ability to communicate effectively with domestic stakeholders, explain technical concepts clearly, and facilitate smooth alignment.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

SQLPythonETLELTdata transformationdata modelingdata pipelinesworkflow schedulingBigQuerySnowflake

Soft Skills

communicationcollaborationautonomyproblem-solvingtechnical solutionsvalidationproposing improvements