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 Senior Data Engineer 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.
Responsibilities and Duties
- Design and implement data pipelines to ingest data from multiple source systems using REST APIs or database connections.
- Build and maintain Bronze/Silver/Gold layer transformations ensuring data quality, consistency, and performance.
- Implement data quality checks and cross-system reconciliation logic.
- Develop and optimize SQL queries and transformations using dbt or similar tools.
- Design and implement data models for analytics and reporting use cases (ALM, ERM, regulatory reporting).
- Build REST APIs or data serving layers for downstream consumers.
- Participate in architecture decisions for data platform components.
- Write unit tests, integration tests, and data quality tests for pipelines.
- Monitor data pipeline performance, troubleshoot failures, and implement improvements.
- Optimize query performance through partitioning strategies, Z-ordering, and query tuning.
- Implement infrastructure as code for data platform components using Terraform.
- Set up CI/CD pipelines for automated testing and deployment of data pipelines.
- Mentor mid-level engineers and conduct code reviews.
- Contribute to documentation and best practices for the team.
- Collaborate with backend engineers to define API contracts and data schemas.
- Work with Technical Lead on platform design and technology selection decisions.
- Lead features and initiatives within the data platform.
Required Skills and Experience
- 5+ years of experience in data engineering with data focus or analytics engineering.
- Strong proficiency in SQL and Python.
- Hands-on experience building data pipelines using modern tools (Airflow, Spark, dbt, or similar).
- Experience with cloud data platforms (AWS, Azure, GCP) and storage systems (S3, ADLS, GCS).
- Strong understanding of data modeling techniques including dimensional modeling, data vault, or event-driven architectures.
- Experience with data quality validation and testing frameworks.
- Proven ability to debug and optimize slow queries and data processing jobs.
- Experience with version control (Git) and CI/CD pipelines.
- Understanding of data governance concepts: access control, audit logging, data lineage.
- Strong problem-solving skills and ability to work independently.
- Experience mentoring junior or mid-level engineers.
- Excellent communication skills for collaborating with cross-functional teams.
- Bachelor's degree in Computer Science, 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 in financial services, fintech, or other regulated industries.
- Knowledge of banking domain concepts: core banking systems, payment processing, regulatory reporting, AML/transaction monitoring.
- Experience implementing data platforms that comply with regulatory requirements (FISC Security Guidelines, FSA/BOJ reporting, GDPR, APPI).
- Hands-on experience with the Databricks platform or AWS native data services.
- Experience implementing cross-system reconciliation for financial data.
- Experience with performance tuning: partitioning strategies, query optimization, cost management.
- Experience building REST APIs with Python (FastAPI, Flask, or similar) for data serving.
- Knowledge of streaming data pipelines (Kafka, Kinesis, or similar).
- Experience with Terraform.
- Contributions to open-source data engineering projects.
- Experience with BI tools (QuickSight, Tableau, Looker, PowerBI).
- Experience leading technical initiatives from design through implementation.
- Track record of improving data platform performance or reducing costs (provide specific metrics).
- 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 (Fluent, capable of handling communication with clients in Japanese)
- English: TOEIC score of 700 or above
(Note: If you have other qualifications or experiences demonstrating English proficiency, such as EIKEN Pre-1, EIKEN 2nd Grade (CSE score 1950+), TOEFL iBT 60+, IELTS 5.0+, or Cambridge FCE.), feel free to discuss with us)
For those without a TOEIC 700+ equivalent score, they will be asked to take a designated test during the interview process (generally after the first interview).
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 or Apache Iceberg 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
- Orchestration & Processing:
- Managed workflow orchestration platforms (Amazon MWAA/Apache Airflow, Databricks Workflows, or similar)
- Distributed data processing with Apache Spark
- Serverless compute options for cost optimization
- Streaming and batch ingestion patterns (AutoLoader, scheduled jobs)
- Data Transformation:
- dbt (data build tool) for SQL-based analytics engineering
- Delta Live Tables or AWS Glue for declarative ETL pipelines
- SQL and Python for data transformations
- Incremental materialization strategies for efficiency
- Query & Analytics:
- Serverless query engines (Amazon Athena, Databricks SQL, or Redshift Serverless)
- 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 frameworks (AWS Glue Data Quality, Delta Live Tables expectations, Great Expectations)
- Cross-system reconciliation and validation logic
- Fine-grained access control with column/row-level security (AWS Lake Formation or 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: CloudWatch, Databricks monitoring, or similar
- 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.
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.
| 職種 / 募集ポジション | Senior Data Engineer, Digital Bank, Tokyo |
|---|---|
| 雇用形態 | 正社員 |
| 給与 |
|
| 勤務地 | |
| Salary System | <Salary Range> Min 484,000 JPY / month（5,808,000 JPY / year）〜917,000 JPY / month（11,004,000 JPY / year） Each including fixed allowances of 140,914 JPY〜266,988 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 |
| 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% |