Abbeal

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Tokyo · Permanent · Senior (6-9 yrs)

Senior QA / Integration Test Engineer — Data Platform, Digital Bank (Tokyo)

A new digital bank in Tokyo is hiring its first dedicated integration-test engineer for its data platform (Databricks/Delta Lake): cross-system reconciliation, job orchestration, audit. Must already reside in Japan, business-level Japanese (JLPT N2 or equivalent) required.

  • AWS
  • Databricks
  • Delta Lake
  • Unity Catalog
  • Apache Spark
  • CI/CD Testing
ApplyPermanent contract · According to profile — Tokyo

Role conditions

Japan residency required — this role does not include relocation or visa sponsorship. Applications from outside Japan cannot be considered.

Business-level Japanese required (JLPT N2 or equivalent).

Context

Our client is building a new digital bank in Tokyo, born from a joint venture between a major Japanese fintech player and a leading banking group, with a strong focus on embedded financial products for SMBs.

About the role

As a Senior QA / Integration Test Engineer on the Data Platform team, you will own integration testing for the central data hub connecting most systems inside this new digital bank. The scope covers correctness across the Bronze/Silver/Gold pipeline, job orchestration and recovery, audit/reconciliation, and deployment/security integration — a scope that requires real data engineering depth, distinct from the black-box functional testing already covered by a separate QA team you work closely alongside. This is a senior individual contributor role: you define test strategy, design and execute test plans, and work directly with data engineers to reproduce, prioritize and verify fixes, with minimal day-to-day guidance.

Team

Small agile team of 11 engineers. This role is the first dedicated integration-test hire embedded in that team.

Technology stack and tools

  • Cloud — AWS (Tokyo region), S3 data lake, VPC networking, IAM
  • Databricks lakehouse — Delta Lake (ACID, time-travel, schema evolution), Bronze/Silver/Gold medallion architecture, Unity Catalog
  • Orchestration & processing — Databricks Workflows, Apache Spark, batch ingestion with AutoLoader
  • Data quality & governance — Delta Live Tables expectations, cross-system reconciliation, column/row-level security via Unity Catalog, automated lineage, audit logging and 10-year retention
  • Dev & test tooling — SQL, Python for test scripts and data validation, Databricks (notebooks, workflows, SQL), GitHub, GitHub Actions, JIRA + Confluence, AI-assisted tooling (Claude Code, GitHub Copilot)

Responsibilities

  1. Design and execute integration tests validating Bronze → Silver → Gold pipeline correctness: cross-source reconciliation, grain/history/referential integrity, cross-layer entity assembly
  2. Validate downstream interface generation and delivery (field mapping, file structure/layout, secure transfer) to internal consumers and regulatory reporting
  3. Test job orchestration and execution management: scheduling and business-day calculation, job dependencies, parallel execution/locking, job lifecycle status transitions
  4. Test retry, rerun, backfill and recovery mechanisms: automatic retry, manual rerun, partial failure recovery, historical backfill, source-correction propagation
  5. Validate audit, control and reconciliation mechanisms: batch control IDs, record-count and amount reconciliation across layers, data lineage tracing, audit integrity
  6. Test monitoring/alerting for job failures, data anomalies and monitoring self-health, coordinating with the QA team on alert routing/escalation
  7. Validate deployment completeness, configuration and environment isolation (DEV/TEST/PROD), rollback safety, code/schema version compatibility
  8. Test security and privacy controls: least-privilege service accounts, PII handoff boundaries, masking/encryption, credential rotation, data retention/deletion propagation
  9. Define test plans, test cases and acceptance criteria per integration test category, based on architecture and business requirements
  10. Write automated data validation checks (SQL, Python, Delta Live Tables expectations) so integration tests are repeatable and run in CI/CD
  11. Track defects, work directly with data engineers to reproduce, prioritize and verify fixes
  12. Collaborate with the QA team on the shared Dev/QA test boundary (alert content/routing, escalation) to avoid coverage gaps
  13. Read and interpret Japanese-language test scope documentation and specifications, communicate findings with Japanese-speaking QA and business stakeholders
  14. Document test coverage, results and known issues for each phase of the integration test plan

Profile

  • Currently based in Japan with valid work authorization — no relocation or visa sponsorship from overseas for this role
  • Business-level Japanese required (JLPT N2 or equivalent)
  • 5+ years in QA/test engineering, including meaningful hands-on experience testing data pipelines, ETL/ELT processes, or data warehouse/lakehouse systems (not application/UI testing alone)
  • Strong SQL; working knowledge of Python for test scripts and data validation checks
  • Understanding of layered/medallion pipeline architectures, data reconciliation, referential integrity
  • Experience testing job orchestration/scheduling systems including failure, retry and recovery scenarios
  • Structured QA methodology: test plan and test case design, defect tracking, traceability
  • Familiarity with data security/privacy testing: access control, PII handling, encryption, audit logging
  • Comfortable reading technical and business documentation and communicating test findings in Japanese
  • Bachelor's degree in CS, Engineering or related, or equivalent practical experience

Nice to have

English business level · financial services / fintech / regulated industries · Databricks or similar lakehouse + Delta Lake concepts · testing file-based interfaces (SFTP, HULFT) or API-based data exchange · JSTQB or equivalent QA certification · CI/CD pipelines and test automation frameworks · banking domain (core banking, payments, regulatory reporting) · owning a shared test boundary across two teams without gaps or duplication.

Growth path

Potential to grow into a QA/test lead role owning test strategy across the full platform, including the domain-based QA team scope. Regular 1-on-1s with PM and Tech Lead. Path to specialize in data quality engineering or platform test automation, or toward data engineering given the skill overlap.

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Senior QA / Integration Test Engineer — Data Platform, Digital Bank (Tokyo)