Data Engineer

Overview

We are seeking a skilled Data Engineer to join the PDP team and contribute to building scalable, reliable data pipelines that power PayPal's payments ecosystem. You will work on high-volume data processing, real-time eventing, and analytics infrastructure that directly impacts PayPal's financial operations and business intelligence.

Responsibilities

Key Responsibilities

• Design, develop, and maintain large-scale data pipelines processing millions of payment events daily
• Build and optimize Apache Spark jobs for batch and streaming data processing
• Develop complex SQL queries and transformations for data analysis and reporting
• Implement data models and schemas in GCP BigQuery for analytics and downstream consumption
• Ensure data quality, completeness, and correctness through validation and reconciliation frameworks
• Collaborate with cross-functional teams (Finance, Risk, Analytics) to understand data requirements and deliver solutions
• Troubleshoot and resolve data pipeline issues with minimal supervision
• Contribute to platform modernization and cloud migration initiatives
• Participate in code reviews, design discussions, and technical documentation
  
  
  

• Experience: 3+ years of experience as a Data Engineer or similar role
• Apache Spark: Proven hands-on experience with Spark for big data processing (Spark SQL, DataFrames, Datasets)
• SQL: Strong ability to write complex SQL queries for data manipulation, transformation, and analysis
• Programming: Expertise in Scala (highly preferred) or Python
• Cloud Data Stores: Experience with Google Cloud Platform (GCP), particularly BigQuery for data warehousing and analytics
• Problem Solving: Excellent analytical and problem-solving skills with ability to work independently with minimal support
  
  
  

• GCP certification (e.g., Professional Data Engineer)
• Familiarity with distributed systems concepts and architecture
• Experience with big data processing tools and techniques (Kafka, Pub/Sub, Dataflow)
• Experience with real-time streaming data pipelines
• Knowledge of data modeling and schema design best practices
• Exposure to AI/ML concepts and applications
• Experience in payments, fintech, or financial services domain