Senior Data Engineer - MIDAS Data Platform, 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:** Design and implement data pipelines to ingest data from multiple source systems (CRM, CBS, CLM, LOS) 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 (e.g., validating CBS transaction records against ledger balances) Develop and optimize SQL queries and transformations using Databricks SQL/notebooks or Delta Live Tables Design and implement data models for analytics and reporting use cases, with a primary focus on CRM data integration, alongside regulatory reporting and the outbound Conseek risk-export mart (ALM/ERM risk computation itself is handled externally by Conseek) 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 Support EOD (End-of-Day) data collection processes that align with Zengin settlement timing Requirements 5+ years of experience in data engineering or analytics engineering Strong proficiency in SQL and Python Hands-on experience building data pipelines using modern tools (Databricks, Spark, 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 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 Language ability: Japanese at Business level required Nice to haves While not specifically required, tell us if you have any of the following. English proficiency (Business level or above, e.g. TOEIC 700+) is a plus for cross-team documentation and collaboration Experience with data quality validation and testing frameworks 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 (FI SC Security Guidelines, FSA/BOJ reporting, GDPR, APPI) Hands-on experience with Databricks platform (AutoLoader, Unity Catalog, Delta Live Tables, Databricks SQL, Databricks Workflows) Experience implementing cross-system reconciliation for financial data Experience with performance tuning on Databricks: partitioning strategies, Z-ordering, query optimization, cost management Experience building REST APIs with Python (FastAPI, Flask, or similar) for data serving Knowledge of streaming data ingestion patterns and external tools (Kafka, Kinesis) Experience with Terraform Contributions to open-source data engineering projects Experience with Databricks SQL Dashboards or BI tools (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 is at a major turning point, shifting “from Cloud to AI.” We are currently driving “AX (AI Transformation)”—the next step beyond DX—with the goal of providing “Digital Workers,” where AI agents autonomously execute tasks. As we enter a phase of evolving into Japan’s No. 1 back-office AI company by integrating AI agents into all of our products in the future, we are looking for individuals who can contribute to AI-driven development and value creation. Compensation ¥6,504,000 ~ ¥11,004,000 annually. **Requirements:** 5+ years of experience in data engineering or analytics engineering Strong proficiency in SQL and Python Hands-on experience building data pipelines using modern tools (Databricks, Spark, 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 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 Language ability: Japanese at Business level required **Nice to have:** While not specifically required, tell us if you have any of the following. English proficiency (Business level or above, e.g. TOEIC 700+) is a plus for cross-team documentation and collaboration Experience with data quality validation and testing frameworks 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 (FI SC Security Guidelines, FSA/BOJ reporting, GDPR, APPI) Hands-on experience with Databricks platform (AutoLoader, Unity Catalog, Delta Live Tables, Databricks SQL, Databricks Workflows) Experience implementing cross-system reconciliation for financial data Experience with performance tuning on Databricks: partitioning strategies, Z-ordering, query optimization, cost management Experience building REST APIs with Python (FastAPI, Flask, or similar) for data serving Knowledge of streaming data ingestion patterns and external tools (Kafka, Kinesis) Experience with Terraform Contributions to open-source data engineering projects Experience with Databricks SQL Dashboards or BI tools (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 is at a major turning point, shifting “from Cloud to AI.” We are currently driving “AX (AI Transformation)”—the next step beyond DX—with the goal of providing “Digital Workers,” where AI agents autonomously execute tasks. As we enter a phase of evolving into Japan’s No. 1 back-office AI company by integrating AI agents into all of our products in the future, we are looking for individuals who can contribute to AI-driven development and value creation. **Compensation:** ¥6,504,000 ~ ¥11,004,000 annually.