Platform Engineer (Kafka Specialist)

📍 Job Overview

• Job Title: Platform Engineer (Kafka Specialist)
• Company: PayPay
• Location: Remote
• Job Type: Full-Time
• Category: DevOps, Infrastructure
• Date Posted: 2025-06-26

🚀 Role Summary

• Lead Kafka platform expansion and modernization efforts to support PayPay's rapid growth and future expansion.
• Strengthen existing Kafka platform to bring a truly event-driven architecture to the development process, adding performance and resilience.
• Migrate self-hosted Kafka clusters to KRaft mode and operate Kafka in both self-managed and AWS MSK environments at scale.

💻 Primary Responsibilities

• Tech Leadership & Architecture: Define and drive Kafka platform strategy, architecture, and best practices.
• Development & Operations: Develop, deploy, and manage highly available Kafka infrastructure, ensuring optimal performance and reliability.
• Monitoring & Alerting: Monitor Kafka clusters for reliability, throughput, and latency, implementing alerting and performance tuning as needed.
• Performance Tuning & Instrumentation: Optimize Kafka clusters and pipelines for maximum throughput and minimal latency.
• Schema Management & Best Practices: Guide application teams in Kafka topic design, schema management, and best practices.
• Data Pipelines & Replication: Contribute to the development of scalable, secure, and observable data pipelines, including data replication between Kafka clusters.
• Infrastructure Automation: Automate infrastructure and operations workflows using infrastructure-as-code tools.
• Cross-Team Collaboration: Partner with application teams to ensure Kafka topics and pipelines meet business needs and technical standards.

🎓 Skills & Qualifications

Education: Bachelor’s or Master’s Degree in Computer Science or a related field.

Experience:

• Kafka: Minimum of 3 years of engineering experience with Apache Kafka in production environments.
• AWS: Familiarity with AWS cloud platform, especially Amazon MSK (Managed Streaming for Kafka).
• Programming: Proficiency in one or more general-purpose programming languages (e.g., Python, Java, Go).
• Infrastructure Automation: Experience with infrastructure automation and configuration management tools, such as Terraform or Ansible.
• Microservices: Understanding of modern system design using microservice architecture.
• Git & CI/CD: Working knowledge of Git and CI/CD tools.

Required Skills:

• Strong hands-on experience with Kafka cluster operations, including setup, tuning, and maintenance.
• Experience with Kafka authentication and authorization operations.
• Experience with AWS cloud platform, especially Amazon MSK.
• 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.
• Working knowledge of Git and CI/CD tools.

Preferred Skills:

• 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 replication 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 operating distributed systems.
• Working experience in a full remote environment.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

• Kafka Projects: Highlight Kafka-related projects, demonstrating your expertise in Kafka cluster operations, schema management, and data pipeline development.
• AWS Projects: Showcase your experience with AWS services, particularly Amazon MSK, and how you've operated Kafka in AWS environments.
• Code Quality: Display your proficiency in one or more programming languages and your ability to write clean, efficient, and well-documented code.
• Infrastructure Automation: Include examples of infrastructure automation projects, demonstrating your experience with tools like Terraform or Ansible.

Technical Documentation:

• Kafka Tuning & Optimization: Document your approach to Kafka cluster tuning, performance optimization, and fault tolerance strategies.
• Data Pipeline Design: Showcase your ability to design and implement scalable, secure, and observable data pipelines.
• AWS & Infrastructure Management: Detail your experience managing AWS resources, including Amazon MSK and other relevant services.

💵 Compensation & Benefits

Salary Range: $150,000 - $200,000 USD (based on experience and skills)

Benefits:

• Social Insurance (health insurance, employee pension, employment insurance, and compensation insurance)
• 401K
• Translation/Interpretation Support
• VISA Sponsor
• Relocation Support

Working Hours: Super Flex Time (No Core Time) - 9:00am-5:45pm + 1h break (actual working hours: 7h45m + 1h break)

🎯 Team & Company Context

🏢 Company Culture

Industry: Fintech

Company Size: Medium (69M+ users)

Founded: 2018

Team Structure:

• The Streaming Platform team is expanding to support PayPay's growing product and future expansion.
• The role involves close collaboration with application teams to guide Kafka topic design, schema management, and best practices.

Development Methodology:

• Agile/Scrum methodologies and sprint planning for web projects.
• Code review, testing, and quality assurance practices.
• Deployment strategies, CI/CD pipelines, and server management.

Company Website: PayPay

📝 Enhancement Note: PayPay's culture values innovation, risk-taking, and continuous learning. The company encourages employees to challenge themselves and grow professionally in a dynamic and fast-paced environment.

📈 Career & Growth Analysis

Web Technology Career Level: Senior Platform Engineer (Kafka Specialist)

Reporting Structure: The role reports directly to the team lead and works closely with application teams and other infrastructure engineers.

Technical Impact: The Platform Engineer (Kafka Specialist) has a significant impact on PayPay's data streaming infrastructure, ensuring high performance, reliability, and scalability for over 69 million users.

Growth Opportunities:

• Technical Leadership: Develop and mentor junior engineers, contributing to the growth and success of the Streaming Platform team.
• Architecture & Design: Gain exposure to modern system design and architecture, driving Kafka platform evolution and best practices.
• Emerging Technologies: Explore and integrate emerging technologies into PayPay's data streaming infrastructure, staying at the forefront of industry trends.

📝 Enhancement Note: PayPay's rapid growth and expansion present numerous opportunities for career progression and technical skill development. The company encourages employees to take on new challenges and grow both personally and professionally.

🌐 Work Environment

Office Type: Hybrid Workstyle (flexible working style including Remote and office)

Office Location(s): PayPay's headquarters are in Tokyo, Japan, with remote work options available.

Workspace Context:

• Remote Work: PayPay offers a flexible remote work environment, allowing engineers to work from home or in the office as needed.
• Office Facilities: PayPay's offices are designed to foster collaboration and creativity, with state-of-the-art technology and comfortable workspaces.
• Team Interaction: The company encourages regular team interaction and collaboration, both in-person and remotely.

Work Schedule: Super Flex Time (No Core Time) - 9:00am-5:45pm + 1h break (actual working hours: 7h45m + 1h break)

📝 Enhancement Note: PayPay's flexible work arrangements and remote-friendly culture enable engineers to maintain a healthy work-life balance while supporting the company's growth and success.

📄 Application & Technical Interview Process

Interview Process:

1. Phone Screen: A brief phone call to discuss your background, experience, and career goals.
2. Technical Deep Dive: A detailed technical conversation focused on your Kafka expertise, AWS experience, and problem-solving skills.
3. Behavioral & Cultural Fit: An assessment of your cultural fit with PayPay's values and work environment.
4. Final Decision: A final decision based on the previous interviews and a review of your portfolio and references.

Portfolio Review Tips:

• Kafka Projects: Highlight your most impactful Kafka projects, demonstrating your expertise in cluster operations, schema management, and data pipeline development.
• AWS Projects: Showcase your experience with AWS services, particularly Amazon MSK, and how you've operated Kafka in AWS environments.
• Code Quality: Display your proficiency in one or more programming languages and your ability to write clean, efficient, and well-documented code.
• Infrastructure Automation: Include examples of infrastructure automation projects, demonstrating your experience with tools like Terraform or Ansible.

Technical Challenge Preparation:

• Brush up on your Kafka and AWS knowledge, focusing on recent updates and best practices.
• Practice problem-solving exercises and coding challenges related to Kafka and AWS.
• Familiarize yourself with PayPay's products, technology stack, and company culture.

ATS Keywords: Apache Kafka, AWS, Terraform, Ansible, Linux Administration, Java, Python, Go, Microservices, Git, CI/CD, Kafka Connect, Kafka Streams, Data Pipelines, Infrastructure Automation, Monitoring

📝 Enhancement Note: PayPay's interview process is designed to assess your technical expertise, problem-solving skills, and cultural fit. The company values transparency, open communication, and collaboration throughout the interview process.

🛠 Technology Stack & Web Infrastructure

Frontend Technologies: N/A (Platform Engineer role)

Backend & Server Technologies:

• Apache Kafka
• Amazon MSK (Managed Streaming for Kafka)
• AWS (Amazon Web Services)
• Terraform
• Ansible
• Linux Administration
• Java, Python, Go (programming languages)

Development & DevOps Tools:

• Git
• GitHub
• GitHub Actions
• Jenkins
• CI/CD pipelines
• Infrastructure-as-code tools (e.g., Terraform, Ansible)
• Monitoring tools (e.g., Prometheus, Grafana, Victoria Metrics)
• Log aggregation and processing tools (e.g., Logstash, Fluent-bit, Vector)

Database Technologies: N/A (Platform Engineer role)

Cloud Platforms: AWS (Amazon Web Services)

Containerization & Orchestration: Docker, Kubernetes, ArgoCD, Argo rollouts, Argo workflows

Infrastructure & Deployment: AWS (Amazon Web Services), GCP (Google Cloud Platform)

CI/CD & Deployment: GitHub Actions, Jenkins, ArgoCD, Argo rollouts, Argo workflows

Monitoring & Logging: Prometheus, Grafana, Victoria Metrics, Logstash, Fluent-bit, Vector

Collaboration & Communication: Slack, Zoom, Confluence, JIRA

👥 Team Culture & Values

Web Development Values:

• Innovation: Embrace continuous learning and experimentation to drive Kafka platform evolution and best practices.
• Performance: Prioritize optimal performance, reliability, and scalability in Kafka cluster operations and data pipeline design.
• Collaboration: Work closely with application teams to ensure Kafka topics and pipelines meet business needs and technical standards.
• Quality: Maintain high coding standards and documentation practices to ensure knowledge sharing and easy onboarding.

Collaboration Style:

• Cross-Functional Integration: Collaborate with application teams, designers, and stakeholders to ensure Kafka topics and pipelines align with business objectives and user experience requirements.
• Code Review Culture: Foster a culture of code review and peer programming to maintain high-quality code and share knowledge among team members.
• Knowledge Sharing: Encourage regular knowledge sharing, technical mentoring, and continuous learning to drive team growth and success.

📝 Enhancement Note: PayPay's culture values innovation, collaboration, and continuous learning. The company encourages employees to challenge themselves, take on new responsibilities, and grow both personally and professionally.

🌐 Challenges & Growth Opportunities

Technical Challenges:

• Kafka Cluster Management: Optimize Kafka cluster performance, reliability, and scalability to support PayPay's growing user base and data processing requirements.
• AWS & Infrastructure Management: Effectively manage AWS resources, including Amazon MSK and other relevant services, to ensure optimal performance, security, and cost-efficiency.
• Data Replication & Synchronization: Implement seamless data migration, disaster recovery, and cross-region data synchronization strategies to ensure data availability and business continuity.
• Security & Compliance: Implement robust security measures, including authentication, authorization, and encryption, to protect sensitive data and ensure compliance with industry standards and regulations.

Learning & Development Opportunities:

• Technical Leadership: Develop and mentor junior engineers, contributing to the growth and success of the Streaming Platform team.
• Architecture & Design: Gain exposure to modern system design and architecture, driving Kafka platform evolution and best practices.
• Emerging Technologies: Explore and integrate emerging technologies into PayPay's data streaming infrastructure, staying at the forefront of industry trends.
• Soft Skills Development: Enhance your communication, leadership, and project management skills to drive team success and support PayPay's growth and expansion.

📝 Enhancement Note: PayPay's rapid growth and expansion present numerous opportunities for career progression and technical skill development. The company encourages employees to take on new challenges and grow both personally and professionally.

💡 Interview Preparation

Technical Questions:

• Kafka Fundamentals: Demonstrate a deep understanding of Kafka internals, including broker tuning, partitioning, replication, and fault tolerance.
• AWS & Infrastructure: Showcase your experience with AWS services, particularly Amazon MSK, and how you've operated Kafka in AWS environments.
• Problem-Solving: Solve complex technical problems related to Kafka cluster management, data pipeline design, and infrastructure automation.

Company & Culture Questions:

• Company Culture: Demonstrate your understanding of PayPay's culture, values, and work environment, and how you can contribute to the team's success.
• Team Dynamics: Show your ability to work effectively in a remote and hybrid team environment, collaborating with team members across different time zones and cultures.
• Adaptability: Explain how you've adapted to new technologies, tools, or work environments in previous roles, and how you'll approach learning and growth at PayPay.

Portfolio Presentation Strategy:

• Kafka Projects: Highlight your most impactful Kafka projects, demonstrating your expertise in cluster operations, schema management, and data pipeline development.
• AWS Projects: Showcase your experience with AWS services, particularly Amazon MSK, and how you've operated Kafka in AWS environments.
• Code Quality: Display your proficiency in one or more programming languages and your ability to write clean, efficient, and well-documented code.
• Infrastructure Automation: Include examples of infrastructure automation projects, demonstrating your experience with tools like Terraform or Ansible.

📝 Enhancement Note: PayPay's interview process is designed to assess your technical expertise, problem-solving skills, and cultural fit. The company values transparency, open communication, and collaboration throughout the interview process.

📌 Application Steps

To apply for this Platform Engineer (Kafka Specialist) position at PayPay:

1. Submit Your Application: Click on the "Apply Now" button on the job listing and complete the application form.
2. Prepare Your Portfolio: Highlight your most impactful Kafka projects, demonstrating your expertise in cluster operations, schema management, and data pipeline development. Include examples of infrastructure automation projects, showcasing your experience with tools like Terraform or Ansible.
3. Tailor Your Resume: Emphasize your relevant experience, skills, and achievements related to Kafka, AWS, and infrastructure automation. Optimize your resume for web technology keywords to improve visibility with Applicant Tracking Systems (ATS).
4. Prepare for Technical Interviews: Brush up on your Kafka and AWS knowledge, focusing on recent updates and best practices. Practice problem-solving exercises and coding challenges related to Kafka and AWS. Familiarize yourself with PayPay's products, technology stack, and company culture.
5. Research the Company: Learn about PayPay's mission, values, and work environment. Understand the company's products, technology stack, and industry position to demonstrate your enthusiasm and fit for the role.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and web technology industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.