Data Scientist
Credit Key- Full Time
- Junior (1 to 2 years)
The ideal candidate should possess at least three years of experience building complex data pipelines and working with both technical and business stakeholders, along with experience in at least one primary language (e.g., Java, Scala, Python) and SQL, and experience with technologies like BigQuery, Spark, AWS Redshift, Kafka, or Kinesis streaming. They should also have experience creating and maintaining ETL processes, designing, building, and operating a DataLake or Data Warehouse, and possess strong fundamentals in big data and machine learning, and experience with DBMS and SQL tuning.
This Data Engineer will be responsible for designing, building, and maintaining distributed batch and real-time data pipelines and data models, facilitating real-life actionable use cases leveraging data with a user- and product-oriented mindset, supporting teams without data engineers with building decentralized data solutions and product integrations, for example around DynamoDB, enforcing privacy and security standards by design, and working across a variety of engineering specialties such as Data Science and Machine Learning.
Digital payments platform for various clients
PayPal offers a digital payments platform that allows users to conduct online transactions, mobile payments, and peer-to-peer transfers. It generates revenue primarily through transaction fees charged to merchants and provides various services for individual consumers, small to medium-sized businesses, and large enterprises. PayPal distinguishes itself from competitors by offering a wide range of secure financial services tailored to different client needs. The company's goal is to create a convenient and secure digital payments experience for all users.