Sr. Data Engineer - Data Platform

Requirements:

• 5+ years of professional experience in backend or data engineering, with expertise in the following:
• Must have: backend development experience (at least 3~5 years)
• Nice to have: TypeScript / Node.js : Ability to write production-grade code.
• Experience implementing and refactoring within a large monorepo and shared libraries.
• SQL and relational data modelling: Advanced SQL, schema design, judgment on normalisation versus denormalisation, and index design. Able to articulate entity relationships and their business meaning.
• Operating and tuning RDBMS: In MySQL-compatible environments (Aurora MySQL, TiDB, etc. ), reading execution plans, fixing slow queries, assessing the impact of new indexes, and running DDL safely against large tables.
• Reading existing systems: Able to trace data access paths and dependencies through a large, under-documented codebase and turn them into diagrams and documentation.
• Testing and CI: Experience identifying and fixing the root causes of flaky tests (parallel execution conflicts, state leakage such as singleton leakage, and insufficient isolation of external dependencies such as Redis). Working experience with CI (GitHub Actions, etc. ) and containers (Docker).
• Measurement-driven optimisation: Experience designing your own benchmarks or profiles and demonstrating improvement quantitatively.
• Cloud: Professional AWS experience (primarily Aurora/RDS, S3, IAM, and networking).
• Operations and reliability: Professional experience with monitoring and alert design, on-call, incident response, and root cause analysis.

Preferred Qualifications:

• Distributed SQL databases: Experience operating and tuning distributed SQL databases such as TiDB (practical understanding of GC, region splitting, chunk sizing, and similar).
• Data warehouse: Experience building aggregation pipelines on Snowflake and designing or operating reverse-ETL (writing results from the warehouse back into an operational database).
• Retention and privacy: Experience designing and executing production data deletion under a retention policy. PII classification and data design informed by Japan's Act on the Protection of Personal Information (APPI) or the GDPR.
• Automating lineage: Experience extracting data lineage automatically (e. g., via static code analysis) and generating documentation with Mermaid / D2.
• Infrastructure as Code: Experience managing infrastructure as code with Terraform, AWS CDK / CloudFormation, etc.
• Legacy modernisation projects: Experience splitting a monolith, dismantling a shared library, or completing a phased migration without service interruption.
• Documentation practice: Day-to-day use of ADRs, design docs, and runbooks.
• Vendor collaboration: Experience collaborating with database or warehouse vendor specialists on decisions with real technical consequences.
• Community involvement: Contributions to OSS, technical writing, and speaking at meetups or conferences.