MTS 1, Software Engineer

What you need to know about the role-
We re seeking a skilled Software Engineer to design and optimize data storage solutions for large-scale, real-time streaming systems. You will focus on building scalable, low-latency datastores to support high-throughput data pipelines, working closely with cross-functional teams to deliver real-time data insights and ensure system reliability.

Meet our team
The Data Services and Caching group team is responsible for providing the Data access capabilities for PayPal developers. We design, develop, enhance components that get called across every interaction between PayPal components and datastores. We are responsible for scalability, high availability, and reliability of datastores utilized within PayPal.

• Ownership and strive for excellence in your role.
• Own implementation of a module/application/product
• Must be able to work independently and guide the team to define, design, implement, test, release

• Identify and develop solutions to enhance the scalability, high availability, and reliability of datastores

• Design and implement distributed data storage systems optimized for real-time streaming.
• Build scalable, fault-tolerant data pipelines using tools like Kafka, Flink, and Pulsar.
• Manage and optimize data persistence with NoSQL, in-memory stores, and distributed file systems (e.g., Cassandra, Redis, HDFS).
• Ensure low-latency, high-throughput data ingestion and storage.
• Conduct capacity planning and performance tuning for real-time data workloads.
• Collaborate with engineering teams to integrate datastores into real-time applications.
• Work with data scientists to provide fast, reliable access to streaming data.
• Set up monitoring and alerting for datastore performance.
• Implement replication, backup, and disaster recovery strategies.

• BE in Computer Science or Engineering and 6+ years of related industry experience.
• Experience: 3-5+ years with distributed data systems and real-time streaming platforms.
• Strong experience with distributed databases (e.g., Cassandra, MongoDB), streaming platforms (Kafka, Flink), and cloud data stores (DynamoDB, Bigtable).
• Proficiency in Java, Scala, or Python.
• Deep understanding of distributed systems, event-driven architectures, and data modelling for streaming.
• [Good to have] Experience with time-series databases (e.g., InfluxDB), CQRS, and event sourcing.
• [Good to have] Familiarity with Kubernetes, Redis, and performance monitoring tools.