Job summary
Support operations and maintenance of a cloud-based data platform on Databricks and AWS. The role focuses on non-production pipeline development, log analysis, technical investigation, documentation, and backend operational support, working with sample data and test environments alongside the core engineering team.
Key responsibilities
- Develop and maintain ETL/ELT data pipelines in development and test environments.
- Implement data transformations and validation logic from defined specifications.
- Analyze logs to identify failures, anomalies, and performance issues.
- Provide technical findings, code, and documentation to the core team.
- Support testing, schema changes, data onboarding, and regression validation.
- Maintain operational runbooks, documentation, and change logs.
- Collaborate with distributed engineering teams and join regular sync meetings.
Skills and qualifications
- Bachelor’s degree in computer science, engineering, information systems, or equivalent practical experience.
- 5+ years in data engineering or ETL/ELT development.
- Strong SQL and Python.
- Experience with at least one cloud platform (AWS, Azure, or GCP).
- Solid troubleshooting and log analysis.
- Familiarity with workflow orchestration or pipeline tools.
- Databricks, Apache Spark, or Delta Lake experience preferred.
- CI/CD, data onboarding, and distributed or offshore team experience preferred.
Working arrangement
After onboarding, the role moves offshore: remote work while collaborating with the domestic team. Job location is an offshore role with an initial onsite onboarding period in Japan of about 4–6 months.