Software Engineer – Data Engineering

Hybrid 3 Days in Irvine, CA

Our 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. w2

Responsibilities

• Design, 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 Requirements

• 5–8 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).