PayPay is looking for a Data Engineer to build the foundation for our next-gen digital financial platform. You will design and operate large-scale data pipelines using Databricks, AWS, and Terraform. Candidates must have 4+ years of experience and business-level Japanese prof
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PayPay is a FinTech company that has grown to over 70M (as of July 2025) users since its launch in 2018. Our team is hugely diverse with members from over 50 different countries.
OUR VISION IS UNLIMITED_
We dare to believe that we do not need a clear vision to create a future beyond our imagination. PayPay will always stay true to our roots and realize a vision (future) that no one else can imagine by constantly taking risks and challenging ourselves. With this mindset, you will be presented with new and exciting opportunities on a daily basis and have the opportunity to grow and reach new dimensions that you could never have imagined. We are looking for people who can embrace this challenge, refresh the product at breakneck speed and promote PayPay with professionalism and passion.
※ Please note that you cannot apply or be selected in parallel with PayPay Corporation, PayPay Card Corporation and PayPay Securities Corporation.
The assigned organization is primarily advancing projects related to a next-generation digital financial platform. Our team takes the lead in designing, building, and operating modern data engineering infrastructure from scratch to enable data-driven innovation across the group.
※ After joining the company, you are expected to be seconded to PayPay Bank as a member of the above project.
As the business continues to grow rapidly, the importance of data utilization across both PayPay Bank and the broader PayPay Group is increasing. To support product enhancements, marketing initiatives, and fraud detection, establishing a robust data engineering foundation that delivers high reliability, security, and scalability is an urgent task.
Design, develop, and operate robust and scalable data ingestion pipelines using technologies such as Databricks, AWS DMS, and Terraform
Develop large-scale data processing workflows using Spark, Python, and SQL
Design and build data integration platforms that connect banking services, payment systems, internal business applications, and external data sources
Optimize data pipelines by combining Change Data Capture (CDC), streaming, and batch processing architectures
Build and maintain data lakehouse and data catalog platforms leveraging Databricks Lakehouse and Unity Catalog
Design and operate data governance capabilities, including data quality management, metadata management, data lineage, access control, and audit logging
Improve performance, optimize costs, and enhance reliability for large-scale data processing environments
Implement SRE and observability practices for data platforms, including monitoring, alerting, dashboards, and incident response
Build, automate, and standardize data infrastructure using Infrastructure as Code (IaC) technologies such as Terraform
Develop and maintain shared frameworks, tools, templates, and CI/CD pipelines to improve the efficiency and consistency of data engineering operations
Partner with product, analytics, risk management, security, compliance teams, and other PayPay Group companies to drive data utilization and business value
Operate and enhance data platforms in compliance with the security, privacy, regulatory, and internal control requirements expected of a financial institution
At PayPay Bank, Data Engineers do far more than simply collect and process data. This role is about building the data foundation that powers the next generation of digital financial services by combining the reliability and trust required of a bank with the speed, scale, and user reach of the PayPay Group.
You will have the opportunity to drive data-enabled innovation that directly supports product development and business growth, while meeting the stringent security, governance, compliance, and auditability requirements expected of a financial institution. Leveraging modern data technologies such as Databricks and Lakehouse architectures, you will help establish a scalable and trusted data platform that enables the organization to make better decisions and deliver better customer experiences.
PayPay Bank’s strengths lie in its ability to develop products in-house from concept through implementation, its marketing capabilities that deliver value to tens of millions of users, and its robust financial and corporate foundations that maintain the trust expected of critical social infrastructure. As a Data Engineer, you will play a key role in supporting these strengths across the organization and contribute to the challenge of redefining what a bank can be in the digital era.
4+ years of professional experience as a Data Engineer, Data Platform Engineer, or in a related role
Hands-on experience designing, building, and operating data lakes, data warehouses, or data lakehouse platforms
Experience processing large-scale datasets using one or more of the following technologies: Databricks, Delta Lake, or Apache Spark
Strong development experience using Python, PySpark, SQL, or related technologies
Experience with workflow orchestration tools such as Airflow, Dagster, or Prefect
Experience developing and operating cloud-based systems on AWS
Experience building and managing infrastructure using Infrastructure as Code (IaC) tools such as Terraform
Proven experience designing and improving large-scale data pipelines with a focus on performance, reliability, availability, and operational excellence
Business-level Japanese proficiency (native-level or equivalent to JLPT N1/N2)
Experience building and operating data platforms within financial domains such as banking, fintech, payments, credit, securities, or insurance
Experience with event-driven data architectures and streaming data processing using technologies such as Kafka
Experience with Change Data Capture (CDC) tools such as Canal, Debezium, or Maxwell
Experience with data cataloging, access management, and metadata management solutions such as Unity Catalog or AWS Lake Formation
Experience improving monitoring and observability using tools such as Prometheus, Grafana, Datadog, or Amazon CloudWatch
Experience designing, building, and operating CI/CD pipelines using tools such as GitHub Actions or Jenkins
Experience operating cloud-native platforms using Kubernetes, Amazon EKS, Argo CD, or related technologies
Experience with data quality management, data lineage, data contracts, and master data management (MDM)
Experience designing access controls, encryption, data masking, and audit logging for systems handling personal data, sensitive information, or financial transaction data
Experience establishing data engineering standards, development guidelines, shared libraries, and engineering best practices
Experience leading engineering teams, driving technology selection, conducting architecture reviews, and mentoring engineers
Business-level English communication skills
Proven experience integrating AI-assisted development practices into system design, software development, and delivery processes
Contributions to AI-related open-source projects and/or experience building workflow automation solutions powered by AI technologies
金融機関、FinTech、決済、クレジット、証券、保険など、金融ドメインでのデータ基盤開発経験
Kafkaなどを用いたイベント駆動型データ連携、ストリーミング処理の経験
Canal、Debezium、MaxwellなどのCDCツールの利用経験
Unity Catalog、AWS Lake Formationなどを用いたデータカタログ / 権限管理 / メタデータ管理の経験
You are passionate about building user-first financial services and share our commitment to creating better financial experiences for customers
You view data platforms as products and are motivated to improve the productivity and experience of their users, including data engineers, analysts, business teams, and product teams
You can balance the reliability, resilience, and trust required of a financial institution with the speed and agility expected of a fintech company
You think beyond immediate tasks and are able to design architectures and operational models that scale sustainably over the long term
You are comfortable tackling complex challenges, forming hypotheses, driving initiatives independently, and collaborating with stakeholders to achieve outcomes
You see security, governance, and compliance not as constraints, but as essential foundations for enabling trusted and effective data utilization
You are committed to continuous learning, actively explore new technologies, and enjoy sharing knowledge and best practices with your team and the broader organization
In principle, 9:00am-5:45pm + 1h break (actual working hours: 7h45m + 1h break)
Holidays
Every Sat/Sun/National holidays (In Japan)/New Year's break/Company-designated Special days
Paid leave
Annual leave (up to 14 days in the first year, granted proportionally according to the month of employment. Can be used from the date of hire)
Personal leave (5 days each year, granted proportionally according to the month of employment）
＊PayPay's own special paid leave system, which can be used to attend to illnesses, injuries, hospital visits, etc., of the employee, family members, pets, etc.
Salary
Annual salary paid in 12 installments (monthly)
Based on skills, experience, and abilities
Reviewed once a year
Late overtime allowance
※Payroll payment can be changed to digital salary payment “PayPay Paycheck” for an amount set by you
Benefits
Social Insurance (health insurance, employee pension, employment insurance and compensation insurance)
