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# Software Engineer, Data Streaming Systems

- **Company:** Paramount Pictures
- **Location:** Burbank, CA, United States
- **Experience:** Expert
- **Salary:** $124,000.0 - $186,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Automation of Tests, Big Data, Cloud Computing, Cloud Engineering, Software Quality, Distributed Systems, Java Virtual Machine (JVM), Spring Framework, Load Testing, Performance Tuning, Data Streaming, Web Services, Data Logging, Multithreading, Cloud Platform System, Autoscaling, Concurrency, Event Driven Architecture, Build Management, Containerization, Kubernetes, Infrastructure Automation Frameworks, Low Latency, Apache Flink, Real Time Data, Apache Kafka, Reactive Programming, Data Management, Stream Processing, Dynatrace, Docker, Microservices
- **Published:** October 12, 2026
- **Apply:** https://www.juju.com/job/1_viacomcbs-1398353300

## About the Role

Technical Leadership + Lead architectural reviews and mentor engineers in distributed systems best practices. + Drive code quality, documentation, and system design standards. + Advocate for scalable, secure, and maintainable engineering solutions. **Required Technical Skills** Java & Reactive Programming + Advanced proficiency in Java, including concurrency, multithreading, and JVM performance tuning. + Strong experience with reactive frameworks such as Spring WebFlux, Project Reactor, or similar. + Deep understanding of asynchronous, non-blocking system design.
Kafka & Event-Driven Architecture + Extensive experience with Apache Kafka (producers, consumers, streams, schema registry). + Strong understanding of partitioning strategies, offset management, rebalancing, and failure recovery. + Experience designing event schemas and managing schema evolution. + Familiarity with Kafka Streams, Flink, or similar stream-processing frameworks.
Kubernetes & Cloud-Native Systems + Strong hands-on experience deploying and operating applications in Kubernetes. + Experience with containerization (Docker) and microservices architecture. + Knowledge of autoscaling, rolling deployments, and production reliability patterns. **Qualifications** + 5-8 years of experience and strong foundation in distributed systems engineering and event-driven architecture. + Proven track record of building and operating large-scale data streaming systems in production. + Ability to balance architectural rigor with practical delivery timelines. + Excellent problem-solving and collaboration skills. + Self-motivated and committed to engineering excellence. + Paramount is an equal opportunity employer committed to diversity and inclusion. \#LI-PV1 Paramount Streaming, a division within Paramount Global, is the home to the company's direct-to-consumer services spanning free and paid in the form of Pluto TV and Paramount+.

## Description

As a senior engineer, you will shape technical direction, mentor engineers, and drive production-grade reliability across streaming platforms.
This role requires deep expertise in distributed systems, concurrency, and cloud-native microservices. **Primary Responsibilities** Design & Build Real-Time Streaming Applications + Develop high-throughput, low-latency streaming applications using Java and Kafka. + Design event-driven microservices that process, enrich, and route real-time data at scale. + Implement reactive, non-blocking architectures for high concurrency and resilience.
Architect Scalable Distributed Systems + Design and optimize Kafka topics, partitions, consumer groups, and event schemas. + Build horizontally scalable services deployed on Kubernetes. + Contribute to event-driven architecture standards and platform design decisions.
Production Reliability & Performance + Optimize performance for throughput, latency, and resource efficiency. + Implement observability using metrics, logging, and distributed tracing. + Build automated testing strategies for streaming workflows, including integration and load testing. + Participate in on-call rotations and production incident response.
Cloud-Native & Kubernetes Engineering + Deploy and manage containerized services in Kubernetes environments in GCP or similar cloud environments. + Define autoscaling strategies and best practices for resource management. + Develop CI/CD pipelines and Infrastructure as Code practices.
Cross-Functional Collaboration + Partner with Data Engineers to integrate streaming systems with batch pipelines and data platforms. + Work with Software Engineers and Product Managers to expose real-time APIs and services. + Collaborate with AI/ML teams to enable real-time feature pipelines and inference services.