Senior Software Engineer, Data Streaming

This is a Full Time Job

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We’ve got the brands, we’ve got the stars, we’ve got the power to achieve our mission to entertain the planet – now all we’re missing is… YOU! Becoming a part of Paramount means joining a team of passionate people who not only recognize the power of content but also enjoy a touch of fun and uniqueness. Together, we co-create moments that matter – both for our audiences and our employees – and aim to leave a positive mark on culture.

Summary

The Applied Intelligence Data Engineering team seeks a Senior Software Engineer specializing in large-scale, real-time data streaming systems. It builds high-performance, fault-tolerant streaming applications for real-time analytics, APIs, AI workflows, and mission-critical data services.

You will architect distributed, event-driven systems using Java, Kafka, Kubernetes, and modern reactive frameworks. 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.

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.

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