Data Hub Tech Leader, Digital Bank, Tokyo

**About the company:** Money Forward Minato-ku, Tokyo Money Forward is a fintech startup delivering tools to visualize and improve both individuals'​ and companies'​ financial health. **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 Requirements 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 Japanese: Business level English: Business level (TOEIC score of 700 or above) Nice to haves 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 ) Compensation ¥8,004,000 ~ ¥15,000,000 annually. **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 Requirements 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 Japanese: Business level English: Business level (TOEIC score of 700 or above) **Nice to have:** 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 ) **Compensation:** ¥8,004,000 ~ ¥15,000,000 annually.