About PayPay

Minato-ku, Tokyo

With over 47 million registered users (as of May 2022), PayPay is the country’s most popular mobile wallet. Half of all of Japan's smartphone users are using it, and more than 2 billion payments made per year.

Key benefits

  • International engineering team
  • Japanese lessons on company time
  • Incredible scale

About the position

At PayPay, we’re constantly working on improving our systems and processes to be prepared for PayPay’s exponential growth. As a Data SRE at PayPay, we strive towards empowering our developers with the right tools and ensuring high availability, top-notch performance so that our users can have a great experience with our services.

Considering PayPay’s growth, we are looking for experienced SRE who can deliver Observability, Stability and Operations of Data Systems/Pipelines bottlenecks, ensure reliability of the Data Pipelines, Data Lakes, Job Schedulers. Specifically, we are looking for someone who can bring informed and unique viewpoints, enjoy collaborating with a cross-functional team, and is actively pushing boundaries to develop scalable Big Data solutions and positive user experiences.

Responsibilities

  • Define SLOs, SLIs with respect to key indicators like Data Freshness, Data Quality, etc.
  • Design, Support and improve the availability, scalability, stability, reliability, monitoring and alerting & latency of Paypay Data systems
  • Manage day-to-day operations of data services, near real-time and batch data pipelines
  • Create new designs, architectures, standards and methods for large-scale distributed systems

Requirements

  • Knowledge of ingesting, modelling, processing and ETL designs
  • Has, in past demonstrated managing large scale production grade Data Lake, Data Warehouse & ETL systems
  • Should be the Point Person for data integrity/quality within data storage systems and perform root cause analysis & triage issues
  • Should be involved in Data Storage capacity planning, make forecasts, and ability to tune the systems
  • Work with multiple stakeholders across teams to build secure data transfer Qualifications
  • Good understanding of DevOps concepts and implementation
  • Expertise in designing, analyzing, and troubleshooting large-scale distributed systems like Redis, Elasticsearch, Kafka, Hadoop and MySQL
  • Experience in analytical solutions like Looker
  • Experience in Data Lakes like Apache Hudi, Data Warehouse like Big Query and RedShift
  • Knowledge of Spark, Glue, Python and Scala
  • In-depth knowledge and hands-on experience with AWS Cloud Native Data Applications and production workloads.

Nice to haves

These aren’t required, but be sure to mention them in your application if you have them.

  • Knowledge about Microservices
  • Knowledge about observability and how to gather data
  • System design experience and capacity planning for large distributed systems
  • Understanding of Automation tools and implementation
  • Terraform/cloud formation experience
  • Experience with managing monitoring tools like Cloudwatch, NewRelic, etc. Good understanding of DevOps concepts and implementation

Compensation

9 to 12 million JPY annually.

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