Overview
Under the mission of "Money Forward. Move your life forward," Money Forward aims to resolve the financial concerns and anxieties of individuals and businesses through the power of technology.
We have partnered with Sumitomo Mitsui Financial Group, Inc. and Sumitomo Mitsui Banking Corporation to establish a new company in preparation for the launch of a new digital bank.
We are currently seeking candidates for the position of Data Hub Tech Leader as part of this initiative.
*Based on the press release announced on April 16, 2025.
*This position involves employment with Money Forward, Inc., and a secondment to the new company (SMBC Money Forward Bank Preparatory Corporation). The evaluation system and employee benefits will follow the policies of Money Forward, Inc.
Background of the Recruitment
As a Technical Leader for the MIDAS (Management Integration & Data Analytics System) Data Platform Team, you will lead the design and implementation of the core data hub that connects key systems within one of Japan’s innovative digital banks.
You will architect and drive the development of a modern cloud-based data platform that ingests data from multiple banking systems, applies complex business logic, and serves downstream use cases such as enterprise management, regulatory reporting, and risk management.
Operating in a highly regulated banking environment, you will guide the team through complex data engineering challenges including data quality, cross-system reconciliation, time-critical processing, regulatory compliance, and full data traceability.
This is a technical leadership role where you will define the platform architecture, make critical technology decisions, mentor engineers across levels, and establish best practices that shape the platform’s long-term evolution.
Main Responsibilities
- Lead the design and implementation of the MIDAS data platform architecture, making critical technology selections to build our data hub in a simple, safe and maintainable way despite complex business requirements
- Acquire deep domain knowledge in digital banking data flows, including deposits, loans, payments, AML transaction monitoring, regulatory reporting, and Japanese payment systems
- Define and implement data architecture patterns for Bronze/Silver/Gold layers, ensuring data quality, lineage tracking, and auditability for regulatory compliance
- Lead the team as technical architect, mentoring colleagues about technology usage and best architectural approaches
- Design and implement data governance frameworks including access control, PII protection, audit logging, and retention policies aligned with FISC Security Guidelines
- Establish ingestion and ETL patterns for end-of-day data collection and batch processing workflows
- Design data models and APIs to serve downstream consumers
- Drive technical selection roadmap considering cost optimization, scalability, performance requirements, and cloud migration flexibility
- Conduct technical reviews and establish engineering best practices for data pipeline development
- Set up and monitor cost, security, and performance metrics for the data platform
- Collaborate with Product Owner and Project Manager to translate business requirements into technical solutions
- Work with backend engineering teams to define API contracts for data ingestion from core banking, customer management, and loan origination systems
- Implement data quality reconciliation across multiple source systems
- Lead incident response for data pipeline failures and establish SLAs for data availability
- Champion best practices for data security, privacy, and compliance in a regulated banking environment
Required Skills and Experience
- 8+ years of experience in data engineering, data architecture, or analytics engineering with at least 2 years in technical leadership roles
- Proven track record of designing and implementing large-scale data platforms using Databricks on AWS
- Strong understanding of data modeling techniques: dimensional modeling, data vault, and event-driven architectures
- Hands-on experience with Databricks Workflows
- Experience implementing data governance, security, and compliance controls in regulated industries (financial services, healthcare, or similar)
- Knowledge or hands-on experience in at least one banking domain area: core banking systems, payment systems, regulatory reporting, AML/transaction monitoring, or accounting
- Proven ability to make architecture decisions considering trade-offs between cost, performance, scalability, and maintainability
- Experience leading and mentoring engineering teams (3-10 people), conducting code reviews, and establishing engineering best practices
- Strong programming skills in SQL and Python
- Experience with Infrastructure as Code (Terraform, CloudFormation) and CI/CD pipelines for data platforms
- Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field, or equivalent practical experience
Preferred Skills and Experience
While not specifically required, tell us if you have any of the following.
- Experience building data platforms in Japanese financial institutions, with knowledge of FISC, FSA, and BOJ requirements
- Knowledge of Japanese payment systems (Zengin, BOJ-NET) and settlement processes
- Knowledge of data quality frameworks and cross-system reconciliation for financial data
- Understanding of banking data models (GL, trial balance, customer 360, product catalogs, etc.)
- Experience designing secure REST APIs with authentication, rate limiting, and SLA management
- Experience with data lineage tracking and data catalog solutions
- Knowledge of data privacy regulations (GDPR, APPI) and data masking/anonymization techniques
- Proven ability to optimize infrastructure costs while maintaining performance
- Experience with DataOps practices, including testing, observability, and incident response
- Ability to clearly explain technical decisions to non-technical stakeholders and executives
- Experience in AI development and/or experience in using AI tools to improve development processes.Money Forward recently announced our AI Strategy roadmap which focuses on improving AI-driven operational efficiencies, as well as integrating AI agents into our products to deliver better value to our users. (More information here)
Language Requirements
- Japanese: Business level
- English: Business level (TOEIC score of 700 or above)
Technology Stack
- Cloud Infrastructure
- AWS (primary cloud platform in Tokyo region)
- S3 for data lake storage with VPC networking for secure connectivity
- AWS IAM for security and access management
- Data Lakehouse Architecture
- Modern lakehouse architecture using Delta Lake for ACID transactions, time-travel, and schema evolution
- Columnar storage formats (Parquet) optimized for analytics
- Bronze/Silver/Gold medallion architecture for progressive data refinement
- Partition strategies and Z-ordering for query performance
- Unity Catalog for centralized governance and metadata management
- Orchestration & Processing
- Databricks Workflows for managed workflow orchestration
- Distributed data processing with Apache Spark on Databricks clusters
- Serverless compute and auto-scaling clusters for cost optimization
- Streaming and batch ingestion patterns with Databricks AutoLoader
- Data Transformation
- dbt (data build tool) for SQL-based analytics engineering
- Delta Live Tables for declarative ETL pipelines with built-in data quality
- SQL and Python for data transformations
- Incremental materialization strategies for efficiency
- Query & Analytics
- Databricks SQL for high-performance analytics queries
- Serverless and auto-scaling SQL warehouses for variable workloads
- Auto-scaling compute for variable workloads
- Query result caching and optimization
- REST APIs for data serving to downstream consumers
- Data Quality & Governance
- Automated data quality with Delta Live Tables expectations and Great Expectations
- Cross-system reconciliation and validation logic
- Fine-grained access control with column/row-level security using Unity Catalog
- Automated data lineage tracking for regulatory compliance
- Audit logging and 10-year data retention policies
- Business Intelligence
- Amazon QuickSight and/or Databricks SQL Dashboards
- Integration with enterprise BI tools (Tableau, PowerBI, Looker)
Tools Used
- Version Control : GitHub
- CI/CD : GitHub Actions
- Infrastructure as Code : Terraform
- Monitoring : Databricks monitoring, AWS CloudWatch integration
- AI-Assisted Development : Claude Code, GitHub Copilot, ChatGPT
Development Structure
We operate in a small, agile team while collaborating closely with partners from the banking industry. The MIDAS team is growing rapidly, aiming for more than 10 data engineers within this year.
| 職種 / 募集ポジション | Data Hub Tech Leader, Digital Bank, Tokyo |
|---|---|
| 雇用形態 | 正社員 |
| 給与 |
|
| 勤務地 | |
| Salary System | <Salary Range> Min 667,000 JPY / month（8,004,000 JPY / year）- 1,250,000 JPY / month（15,000,000 JPY / year） Each including fixed allowances of 193,649 JPY - 362,852 JPY / month. |
| Bonus | A「High Performance Bonus」may be paid to employees who receive high evaluations based on semi-annual evaluations in addition to their salary. ※Please note that the remuneration of the High Performance Bonus is subject to change according to the company's performance. |
| Probation Period | 3 months from join date |
| Working Hour System | Discretionary Labor System for Professional Work ※Conditions apply; subject to change to Flextime System. |
| Working Hours | 9:30 - 18:30 (60 min break) are the basic working hours. However, employees are able to choose their working hours at their own discretion. ※There is potential for overtime work outside the determined hours. |
| Work Style Policy | Hybrid work style ・As a standard practice, employees are required to work at the office a minimum of 2 days per week. Employees are encouraged to spend 3 or more days in the office. (This policy may be subject to change based on the company and job circumstances) ・The specific "team office days" may vary depending on the assigned team. |
| Holidays/Vacations | ■ Saturdays / Sundays / Japanese national holidays ■ Paid holidays ■ Summer holidays (3 days) ■ Winter holidays (2 days) ■ Year-end and New Year’s holidays (Dec 31st - Jan 3rd) |
| Benefits | ■ Various social insurances (employee pension, health insurance, employment insurance, industrial accident compensation insurance) ■ Neighborhood housing allowance and neighborhood moving allowance ■ Salary-based rent deduction benefit ■ Health check and gynecological checkup ■ Influenza vaccine ■ Book purchases support ■ Defined-contribution corporate pension ■ Employee stock ownership plan ■ Preferential treatment when using the following services（limited to businesses under contract with Money Forward） - Rental agency - Housekeeping services - Babysitting - Online English conversation school |
| Selection Process１ | Casual interview/Document Screening ↓ First interview (Depending on the position, there may be a technical assignment before the interview) ↓ Several interviews (The number of interviews depends on the position) ↓ Final interview (We may ask for a reference check before or after the interview) ↓ Job offer/Offer meeting ※The process may be subject to change depending on the case. |
| Selection Process２ | ■ What are reference checks? Money Forward may ask for your cooperation with reference checks using a reference check service tool. We believe that mutual understanding is limited to the selection process alone. Therefore, we would like to gather information about you from your supervisor and colleagues at your current or former company to ensure a more reliable match and facilitate your early success after joining our company. ※We do not make employment decisions based solely on the contents of reference checks. ※The fact that you are in the selection process with us will not be disclosed to referees. |
| Notes | ・Range of change in job description: Work as determined by the company ・Range of change in work location: Work location as determined by the company |
| Reference Information | https://recruit.moneyforward.com/#introduction |
| Work Environment | At Money Forward, we provide an environment where we can create world-class services together, and we are looking forward to welcoming you. ・Provided PC Specs: We provide PCs equipped with the latest CPUs (MacOS or Windows). Custom-made PCs tailored to business requirements and replacements with the latest OS are also possible. ・Money Forward Library: We have a library system where you can freely borrow books, ranging from technical books to management books. Desired books can be purchased at the company's expense. ・Referral Driven: We cover the cost of recruitment meals. There is a referral reward system. ・Conference Participation Support: The company partially covers participation in domestic and international conferences, such as RubyKaigi and Google I/O. |
| 会社名 | 株式会社マネーフォワード |
|---|---|
| 代表者 | 代表取締役社長グループCEO 辻 庸介 |
| 創業 | 2012年5月 |
| 取締役 | 金坂 直哉 中出 匠哉 竹田 正信 石原 千亜希 |
| 社外取締役 | 田中 正明 倉林 陽 安武 弘晃 宮澤 弦 Ryu Kawano Suliawan 菊間 千乃 |
| 監査役 | 畠山 優実 田中 克幸 瓜生 英敏 |
| CxO・VPox | 瀧 俊雄 山田 一也 坂 裕和 松岡 俊 伊藤 セルジオ 大輔 関田 雅和 松久 正幸 野村 一仁 長尾 祐美子 渋谷 亮 金井 恵子 上利 陽太郎 梅田 康吉 |
| 執行役員 | 田平 公伸 本川 大輔 冨山 直道 木村 友彦 永井 博 駒口 哲也 廣原 亜樹 島村 誠一郎 永井 七奈 木村 慎治 丸山 嘉伸 吉本 憲文 工藤 裕之 島内 広史 小山 幸宏 渡辺 恵伍 松村 道夫 岩崎 大 |
| オフィス | 本社オフィス 〒108-0023 東京都港区芝浦3-1-21 msb Tamachi 田町ステーションタワーS 21F 北海道支社 〒060-0061 北海道札幌市中央区南一条西4-5-1 札幌大手町ビル3階 東北支社 〒980-0021 宮城県仙台市青葉区中央2-2-10 仙都会館 5F 東海支社、名古屋開発拠点 〒450-6213 愛知県名古屋市中村区名駅4-7-1 ミッドランドスクエア 13F 京都支社、京都開発拠点 〒604-8004 京都府京都市中京区三条通河原町東入中島町78番地 明治屋京都ビル 4階 関西支社、大阪開発拠点 〒541-0042 大阪府大阪市中央区今橋 2-5-8 トレードピア淀屋橋 9階 広島支社 〒730-0015 広島市中区橋本町9-7 ビル博丈5F 九州・沖縄支社、福岡開発拠点 〒810-0041 福岡県福岡市中央区大名2丁目6-50 福岡大名ガーデンシティ 16F |
| 社内コミュニケーション活性化の取り組み | ■全社週次/月次朝会/半期総会 ■代表との意見交換会（CEOセッション） ■全社懇親会（MF Happy Hour） ■他部門社員との交流会（シャッフルランチ・ディナー） ■上長との定期1on1（ツキイチ面談） ■社内公募制度（MFチャレンジシステム） ■社員満足度調査（MFグループサーベイ） ※一部正社員のみ |
| 労働条件 | 屋内原則禁煙（喫煙室あり）等 |
| 中途採用比率 | 2021年11月末 93.8％ 2022年11月末 90.0% 2023年11月末 76.6％ 2024年11月末 88.7% |