Senior Data Engineer, 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 using Databricks native tools, as well as REST APIs Build and maintain Bronze/Silver/Gold layer transformations on Databricks 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. Requirements 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 (Databricks, Spark, dbt, or similar). Experience with databricks development and with AWS cloud environments 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. Japanese: Business Level (Fluent, capable of handling communication with clients in Japanese) Nice to haves 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). 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. Compensation ¥5,808,000 ~ ¥11,004,000 annually. **Requirements:** 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 (Databricks, Spark, dbt, or similar). Experience with databricks development and with AWS cloud environments 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. Japanese: Business Level (Fluent, capable of handling communication with clients in Japanese) **Nice to have:** 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). 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. **Compensation:** ¥5,808,000 ~ ¥11,004,000 annually.