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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr Software Engineer - **Company:** PayPal - **Location:** San Jose, CA, United States (Remote available) - **Experience:** Expert - **Salary:** $169,576.0 - $243,500.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), BigTable, BigQuery, Cloud Database, Software Quality, Code Review, Data Mining, Relational Databases, Monitoring of Systems, MySQL, E2e Testing, Cloudera, Software Engineering, Software Project Management, SQL Databases, Data Streaming, Datadog, Data Logging, Data Processing, Google Cloud, Delivery Pipeline, Reliability of Systems, Backend, Build Management, Kubernetes, Information Technology, Apache Kafka, Api Design, Data Pipelines, Api Management, Jenkins - **Published:** August 5, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=241303f0066da89b ## About the Role Minimum Requirements: Master's degree, or foreign equivalent, in Computer Science, Software Engineering, or a closely related field plus three years of experience in the job offered or a related occupation. Employer will accept a Bachelor's degree, or foreign equivalent, in Computer Science, Software Engineering, or a closely related field plus five years of experience in the job offered or a related occupation. Special Skill Requirements: 1. Java programming experience with focus on building decision engine, rule execution systems, and DSL runtime environments (3 years). 2. Experience designing and developing rule-based systems using custom Domain-Specific-Languages (DSL) with ANTLR or equivalent parser-generator frameworks (3 years). 3. Experience designing and implementing Python backend services to support collaborative rule authoring, API development, and platform tooling (3 years). 4. Experience working with relational databases like MySQL and cloud data technologies, including BigQuery and Bigtable for data logging, extraction, transformation and reporting for building reporting systems (3 years). 5. Experience with Google Cloud Platform (GCP) technologies including Google Kubernetes Engine (GKE) and Dataproc for scheduled job processing, to build and operate cloud-native applications at scale (3 years). 6. Experience instrumenting signals via micrometer logging, and setting up dashboards to capture different platform metrics of the rule execution system using monitoring platforms like Datadog or similar data observability platforms (3 years). 7. Experience working with Apache Kafka ecosystem to enable high-throughput, low-latency data streaming for the EDM rule decision platform (2 years). 8. Experience developing end to end testing pipeline, including unit, integration and shadow testing specific to rule flows utilizing CI/CD pipelines like Jenkins/Harness, and Kubernetes deployment creation to trigger shadow testing (2 years). 9. Experience with sound system design and architecture to define non-functional requirements for software project and make reasonable trade-offs while designing systems (2 years). Additional Responsibilities & Preferred Qualifications: EOE, including disability/vets. The base pay for this role will depend on where you work and the relevant experience and expertise you bring. The expected range of pay for this role by location is ## Description PayPal, Inc. seeks Sr Software Engineer in San Jose, CA, Job Duties: Design, develop, and maintain rule-based systems using a custom Domain-Specific Language (DSL) built with ANTLR, including grammar definition, parser generation, and runtime execution. Design and implement decision engine and execution systems in Java to evaluate and process business rules at scale. Design and build Python backend services that power collaborative rule authoring, API integrations, and platform tooling. Engineer high-throughput, low-latency data pipelines using Apache Kafka to enable real-time event streaming and data processing across backend systems. Develop and optimize SQL queries and data models, and leverage cloud data technologies such as BigQuery and Bigtable to support data extraction, transformation, and operational reporting. Design, configure, and manage Kubernetes environments including deployment pipelines, scaling strategies, and cluster operations. Leverage Google Cloud Platform technologies such as Google Kubernetes Engine (GKE) and Dataproc for scheduled jobs to build and operate cloud-native applications. Develop and maintain comprehensive test suites including unit, integration, and end-to-end tests to ensure system reliability and code quality across all platform components. Work with monitoring and observability tools to instrument services, track system health, set up alerts, and diagnose production issues in real time. Participate in on-call rotation to provide operational support for the platform, triage and resolve production incidents, and drive root cause analysis and post-incident reviews. Mentor and guide junior engineers through code reviews, design discussions, and knowledge-sharing sessions, fostering a culture of technical excellence and continuous learning within the team. 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