About PayPay
PayPay is a FinTech company that has grown to over 65M (as of August 2024) 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.
Job Description
PayPay is looking for a Data Engineer for the Credit Modeling team to conceptualize, design and implement improvements to ETL processes and data through independent communication with data-savvy stakeholders.
Responsibilities
- Design, build, and maintain distributed batch and real-time data pipelines and data models.
- Facilitate real-life actionable use cases leveraging our data with a user- and product-oriented mindset.
- Be curious and eager to work across a variety of engineering specialties (i.e., Data Science, and Machine Learning to name a few).
- Support teams without data engineers with building decentralized data solutions and product integrations, for example around DynamoDB.
- Enforce privacy and security standards by design.
Qualifications
- +3 years experience building complex data pipelines and working with both technical and business stakeholders.
- Experience in at least one primary language (e.g., Java, Scala, Python) and SQL (any variant).
- Experience with technologies like BigQuery, Spark, AWS Redshift, Kafka, or Kinesis streaming.
- Experience creating and maintaining ETL processes.
- Experience designing, building, and operating a DataLake or Data Warehouse.
- Experience with DBMS and SQL tuning.
- Strong fundamentals in big data and machine learning.
Preferred Qualifications
- Experience with RESTful APIs, Pub/Sub Systems, or Database Clients.
- Experience with analytics and defining metrics.
- Experience with measuring data quality.
- Experience productionalizing a machine learning workflow; MLOps
- Experience in one or more machine learning frameworks, including but not limited to scikit-learn, Tensorflow, PyTorch and H2O.
- Language ability in Japanese and English is a plus (We have a professional translator but it is nice to have language skills).
- Experience with AWS services.
- Experience with microservices.
- Knowledge of Data Security and Privacy.
- Bilingual Japanese-English
PayPay 5 senses
Working Conditions
Employment Status
Office Location
Work Hours
- Super Flex Time (No Core Time)
- In principle, 10:00am-6:45pm (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, Work from anywhere allowance (JPY100,000)
Benefits
- Social Insurance (health insurance, employee pension, employment insurance and compensation insurance)
- 401K
- Translation/Interpretation support
- VISA sponsor + Relocation support
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Last updated on Aug 22, 2024