Advanced relocation package
About PayPay
PayPay, a FinTech company that has achieved more than 69M users (as of May 2025) since its launch in 2018, is rapidly expanding its business scale as a payment platform used by approximately one out of every two smartphone users in Japan.
The company has a diverse team of professionals from more than 50 countries and is building a world-class engineering organization.
Our biggest competitor is "cash". They are seeking people who can accept this challenge positively, brush up on the product at a tremendous speed that other companies could never achieve, and who are passionate about promoting and spreading such a financial life platform in a short time along with professionalism.
PayPay is committed to maintaining a "Day 1" mindset, bringing to life visions of the future that no one else can even imagine. At PayPay, we provide an environment where everyone can deliver outstanding performance as professionals, through a flexible work style that includes remote and office.
Position
At the core of our architecture in PayPay, we use Kafka for high-performance data streaming, and every payment that goes through the app is handled by multiple topics in Kafka. To keep up with the challenges of our growing product and future expansion, we are expanding our Streaming Platform team and are looking for an engineer with deep experience in Kafka to help lead the next stage.
The role involves strengthening our existing platform to bring a truly event-driven architecture to our development process, while adding performance and resilience to the existing application. A key part of our current roadmap includes migrating our self-hosted Kafka clusters to KRaft mode and operating Kafka both in self-managed form and via AWS MSK. We are looking for someone who is not only hands-on with Kafka internals, but also confident operating it at scale in production environments.
This is a senior role but still very hands-on , an excellent opportunity to build and modernize the streaming infrastructure that powers payments for over 69 million users.
Main Responsibilities
- Tech leadership, architecture, development, and operations for Apache Kafka, including both self-hosted clusters and AWS MSK
- Ensure deployment, management, and smooth operation of highly available Kafka infrastructure
- Monitoring and alerting of Kafka for reliability, throughput, and latency
- Performance tuning and instrumentation of Kafka clusters and pipelines
- Partner with application teams to guide Kafka topic design, schema management, and best practices
- Contribute to the development of scalable, secure, and observable data pipelines
- Automate infrastructure and operations workflows using infrastructure-as-code tools
Tech Stack
| Java, Python, Go
| Kafka, Elasticsearch/Opensearch, AWS MSK, Athena, Glue
| Docker, Kubernetes, ArgoCD, Argo rollouts, Argo workflows, Artifactory, AWS, GCP
| GitHub, GitHub Actions, Jenkins, Terraform, Ansible, Microservices, GitOps
| Logstash, Fluent-bit, Vector, Victoria Metrics, Grafana, Prometheus
| Slack, Zoom, Confluence, JIRA
Your qualification
- Minimum of 3 years of engineering experience with Apache Kafka in production environments
- Minimum of 3 years of experience in AWS, Terraform, Ansible and Linux Administration
- Strong hands-on experience with Kafka cluster operations, including setup, tuning, and maintenance
- Experience with Kafka authentication and authorization operations
- Familiarity with AWS cloud platform, especially Amazon MSK (Managed Streaming for Kafka)
*We heavily rely on AWS, so those without previous AWS experiences must expect to catch up with it after joining us
- Proficiency in one or more general-purpose programming languages (e.g., Python, Java, Go)
- Experience with infrastructure automation and configuration management tools, such as Terraform or Ansible
- Understanding of modern system design using microservice architecture
- Working knowledge of Git and CI/CD tools
Preferred Qualifications
- Deep expertise in running and scaling Apache Kafka both self-hosted and in managed cloud environments (e.g., AWS MSK)
- Experience migrating or operating Kafka in KRaft mode (no ZooKeeper)
- Experience in data replicate between Kafka clusters, enabling seamless data migration, disaster recovery, and cross-region data synchronization
- Exposure to Kafka security, including ACLs, TLS, SASL, and IAM-based auth on MSK
- Deep expertise in Kafka internals, including broker tuning, partitioning, replication, and fault tolerance
- Contributions to Kafka-related open source projects or community involvement
- Experience with Kafka Connect, Kafka Streams, or other stream processing frameworks
- Experience guiding cross-team adoption of Kafka in microservice architectures
- Experience in operating distributed systems
- Working experience in a full remote environment
- Bachelor’s or Master’s Degree in Computer Science or a related field
What we offer
- Social Insurance (health insurance, employee pension, employment insurance and compensation insurance)
- 401K
- Translation/Interpretation support
- VISA sponsor + Relocation support
Additional details
PayPay 5 senses
- Please refer PayPay 5 senses to learn what we value at work.
Working Conditions
Employment Status
- Full Time
Office Location
- Hybrid Workstyle (flexible working style including Remote and office)
*There are no fixed rules regarding office attendance in Product group; it depends on each individual's discretion.
Work Hours
- Super Flex Time (No Core Time)
- In principle, 9:00am-5:45pm (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
- Special Incentive once a year *Based on company performance and individual contribution and evaluation
- Late overtime allowance
*Payroll payment can be changed to digital salary payment “PayPay Paycheck” for an amount set by you
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