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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

PayPay's growth is driving a rapid expansion of PayPay product teams and the need for a robust Data Engineering Platform to support our growing business needs is more critical than ever. We are looking for a Data Engineer for the DaaS team. The DaaS team’s responsibility is to design, implement, and operate this platform by using cutting edge technologies such as Spark, Hudi, Delta Lake, Scala, and AWS suite of data tools.
We are looking for talented Data Engineers to join our team and help us scale our platform across the organizations.

Main Responsibilities

• Design, develop, and maintain scalable data ingestion pipelines using AWS Glue, Step Functions, Lambda, and Terraform
• Optimize and manage large scale data pipelines to ensure high performance, reliability, and efficiency
• Implement data processing workflows using Hudi, Delta Lake, Spark, and Scala
• Maintain and enhance Lakeformation and Glue Data Catalog for effective data management and discovery
• Collaborate with cross-functional teams to ensure seamless data flow and integration across the organization
• Implement best practices for observability, data governance, security, and compliance

Your qualification

• 5+ years experience as a Data Engineer or in a similar role
• Hands-on experience with Apache Hudi, Delta Lake, Spark, and Scala
• Experience designing, building, and operating a DataLake or Data Warehouse
• Knowledge of Data Orchestration tools such as Airflow, Dagster, Prefect
• Strong expertise in AWS services, including Glue, Step Functions, Lambda, and EMR
• Familiarity with change data capture tools like Canal, Debezium, and Maxwell
• Experience with data warehousing tools like AWS Athena, BigQuery, Databricks
• Experience in at least one primary language (e.g. Scala, Python, Java) and SQL (any variant)
• Experience with data cataloging and metadata management using AWS Glue Data Catalog, Lakeformation, or Unity Catalog
• Proficiency in Terraform for infrastructure as code (IaC)
• Strong problem-solving skills and ability to troubleshoot complex data issues
• Excellent communication and collaboration skills
• Ability to work in a fast-paced, dynamic environment and manage multiple tasks simultaneously

What we offer

• Social Insurance (health insurance, employee pension, employment insurance and compensation insurance)
• 401K
• Translation/Interpretation support
• VISA sponsor + d88ÕæÈË support

Additional details

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