Software Engineer – Data Engineering

Hybrid 3 Days in Irvine, CAOur client seeks a hands-on Software Engineer to build and operate high-throughput, highly available distributed backend systems for semiconductor manufacturing data platforms. The role demands strong backend engineering in Java, Scala, Go, or Rust, deep distributed systems fundamentals, and proficiency with cloud-native operations on Kubernetes with GitOps via ArgoCD. The engineer will collaborate with data engineering, infrastructure, and product stakeholders to deliver scalable, resilient, and production-grade services. The work will emphasize performance, reliability, and robust event-driven and streaming data processing.Due to client requirements, applicants must be willing and able to work on a w2 basis. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance.Rate: $70.00 to $80.00/hr. w2ResponsibilitiesDesign, develop, and maintain core backend services and platform components for large-scale data processing and analytics.Build and optimize distributed, highly available systems with focus on throughput, latency, fault tolerance, and scalability.Develop and operate streaming and event-driven data processing applications.Design systems that handle out-of-order, late-arriving, and inconsistent data.Collaborate with data engineering, infrastructure, and product teams to deliver reliable backend services.Deploy and operate services in cloud-native Kubernetes environments.Troubleshoot and resolve complex production issues across application, distributed components, and infrastructure layers.Participate in architecture and design reviews to guide platform and system evolution.Ensure systems meet defined availability, scalability, and performance SLAs.Contribute to Agile practices including sprint planning, technical design discussions, and code reviews.Uphold engineering standards through clean code, documentation, testing, and continuous improvement.Adopt AI-assisted development tools responsibly to enhance velocity and quality.Experience Requirements5–8 years building, deploying, and operating scalable, high-availability distributed systems.Hands-on experience with data-intensive and high-throughput processing systems in production.Experience in cloud environments.Advanced proficiency in software engineering with object-oriented and functional design principles.Hands-on experience with at least two of: Java, Scala, Go, Rust.Strong understanding of microservices architecture, backend design patterns, and best practices.Excellent fundamentals in data structures, algorithms, and core computer science concepts.Proven ability to debug and troubleshoot distributed systems across service and infrastructure layers.Experience designing and consuming RESTful APIs.Strong experience in cloud environments, preferably Azure.Solid understanding of Docker and containerized service design.Hands-on experience running services on Kubernetes, including deployment, scaling, health checks, and resource management.Experience packaging and deploying applications using Helm.Extensive experience with GitOps workflows and tools such as ArgoCD.Strong knowledge of Linux/Unix operating systems.Experience developing streaming or event-driven applications.Familiarity with event streaming platforms such as Kafka or equivalent.Experience with NoSQL databases such as key-value, document, wide-column, graph, time-series, or search.Understanding of data modeling, performance tuning, and scalability tradeoffs.Proficiency with Git and Agile/Scrum development methodologies.Working experience with CI/CD pipelines including build, test, and deployment automation.Comfortable integrating AI-assisted coding tools into daily workflows.Deeper expertise in distributed systems fundamentals such as replication, consensus, leader election, and fault tolerance (preferred).Experience operating mission-critical, 24/7 production systems (preferred).Exposure to DevOps and SRE practices including monitoring, logging, tracing, and observability (preferred).Database internals curiosity or performance optimization experience (preferred).Experience in manufacturing, IoT, telemetry, or large-scale data platforms (preferred).Education Requirements Bachelor’s degree in Computer Science, Computer Engineering, or related field, or equivalent practical experience.Azure experience or certification (preferred).