Money Forward: data backbone of a brand-new digital bank in Tokyo.

Money Forward, Inc. is one of Japan's leading FinTech players, listed on the Tokyo Stock Exchange. The company runs personal-finance solutions (Money Forward ME, 15M+ users) and B2B platforms (Money Forward Cloud — accounting, payroll, invoicing, ERP). Money Forward has partnered with a top-tier Japanese banking group to launch a brand-new digital bank, built fully from scratch.

The challenge

Build, in greenfield, the data backbone of a bank that's just starting up. The platform must ingest data from multiple banking systems (core banking, payments, ledger), apply complex, heavily regulated business logic, and act as the single source of truth for JFSA reporting, AML, risk management and business steering — with zero margin for error from day one.

Our approach

Abbeal embedded a hybrid Data Engineering team in Tamachi (Tokyo), pairing Senior and Mid-Career engineers selected for their dual FinTech / Modern Data Stack expertise. Hybrid mode: 1-2 days a week on-site, the rest remote. Our scope covers:

• Designing and operating Bronze -> Silver -> Gold pipelines (Databricks Workflows, Apache Spark, dbt, Delta Live Tables)
• Standing up the Lakehouse Medallion architecture on Delta Lake, with Unity Catalog governance and end-to-end lineage
• Data quality and cross-system reconciliation (Great Expectations, DLT checks)
• Data modeling (dimensional, data vault, event-driven) for regulatory and analytical reporting
• Full industrialization: Infrastructure as Code (Terraform), CI/CD (GitHub Actions), monitoring (Databricks + AWS CloudWatch)
• Mentoring and code review for the client's internal profiles, with an AI-assisted dev workflow (Claude Code, GitHub Copilot, ChatGPT) baked in daily

The stack

• Cloud & infra: AWS (Tokyo Region) — S3 (Data Lake), VPC, IAM
• Lakehouse: Medallion architecture (Bronze/Silver/Gold), Delta Lake (ACID, time-travel, schema evolution), Parquet, partitioning + Z-ordering, Unity Catalog
• Orchestration & processing: Databricks Workflows, Apache Spark on Databricks (auto-scaling), AutoLoader (batch + streaming)
• Transformations: dbt, Delta Live Tables, SQL & Python, incremental materializations
• Serving & analytics: Databricks SQL + warehouses, REST APIs (FastAPI, Flask)
• Quality & governance: Delta Live Tables checks, Great Expectations, RBAC + row/column controls (Unity Catalog), lineage, audit logs
• BI: Amazon QuickSight, Databricks SQL Dashboards, Tableau / Power BI / Looker
• DevOps: Git/GitHub, GitHub Actions, Terraform, monitoring Databricks + AWS CloudWatch
• AI tooling daily: Claude Code, GitHub Copilot, ChatGPT integrated into the dev workflow

The Abbeal team

• Senior Data Engineer (5+ years): European profile based in Japan, dual FinTech expertise (Nordic payments, banking & insurance) + Data Engineering. Technical lead on Databricks / Spark / Lakehouse, mentoring mid-career teams
• Mid-Career Data Engineer (3+ years): international profile based in Tokyo, specialist in Financial Data Platforms and Modern Data Stack (AWS, Databricks, Airflow, dbt)
• Active hiring pipeline: target 10 people on the Data Platform side, sourcing on Tokyo + remote Japan, several candidates in client interviews

Engagement extension — QA

Following the Data Engineering team's performance, the client opened two new roles via Abbeal: QA Engineer (Mid/Senior, 3-7 years, Python/TS automation, banking/fintech, JLPT N2+) and Lead QA Engineer (7+ years, leadership of 3-6 QAs, interface with Risk & Compliance + JFSA auditors). Scope: core banking workflows, data pipelines, regulatory reporting, KYC/AML, payments, ledger. QA stack: Playwright, Cypress, REST Assured, pytest, k6, Databricks/dbt tests, Great Expectations.

Why Abbeal

A premium tech studio bridging France and Japan, with hubs in Tokyo / Paris / Montreal and an international mobility programme (Mobbeal) that lets us mobilize rare Data + FinTech profiles, already in Japan or ready to relocate. 150+ clients served, 20+ expats via Mobbeal.