Senior Backend Engineer (Golang)

Our client is seeking a seasoned Backend Engineer to design and develop high-performance, cloud-native infrastructure using Go. This role involves building systems for real-time data ingestion, processing, and low-latency trading environments, ensuring reliability, observability, and performance. The engineer will lead technical discussions, mentor team members, and contribute to CI/CD improvements, taking ownership of production services.

Must Have

• Lead the design and development of robust high-performance, cloud-native backend systems using Go.
• Drive engineering excellence through code quality, best practices, and mentorship.
• Take ownership of production services, ensuring reliability, observability, and performance tuning.
• 5+ years of backend development experience, including 3+ years with Go in production-grade systems.
• Experience leading large-scale system design and mentoring engineers.
• Strong knowledge of concurrency, memory management, and performance optimization in Go.
• Proven track record of designing and deploying microservice architectures in high-availability, high-throughput environments.
• Solid understanding of message queues, event-driven architectures, and asynchronous processing.
• Strong understanding of microservice architecture and REST/gRPC APIs.
• Strong understanding of networking data transmission protocols (TCP, UDP, WSS, etc.).
• Experience building and deploying cloud-native applications.
• Familiarity with containerization technologies (Docker) and orchestration engines (e.g., ECS, Kubernetes).
• Proficiency with message brokers (e.g., Kafka) and distributed systems.
• Knowledge of data storage technologies such as PostgreSQL, Redis, and time-series databases.

Our client is seeking a seasoned Backend Engineer to help build high-performance, cloud-native infrastructure to support our research, trading, and data pipelines. This role is crucial to enabling real-time data ingestion and processing workflows, and ensuring our systems can meet the demands of a high-uptime, low-latency trading environment.

What You Will Do

• Lead the design and development of robust high-performance, cloud-native backend systems using Go that support real-time data processing and low-latency workflows.
• Drive engineering excellence through code quality, best practices, and mentorship of other team members.
• Work closely with trading, product, and infrastructure teams to understand system requirements and deliver performant solutions.
• Take ownership of production services, ensuring reliability, observability, and performance tuning. Optimize systems performance and ensure system stability, reliability, and security.
• Contribute to infrastructure automation and CI/CD improvements to support rapid deployment and operational agility.
• Conduct in-depth code reviews, lead technical discussions, and influence engineering culture and standards.
• Implement automated testing, CI/CD pipelines, and participate in code reviews and design discussions.
• Deploy and manage services leveraging cloud-native tools and best practices
• Monitor, debug, and troubleshoot production systems and be a part of the on-call incident response team in a high-uptime environment

What You Will Need

• 5+ years of backend development experience, including 3+ years with Go in production-grade systems.
• Experience leading large-scale system design and mentoring engineers on engineering best practices.
• Strong knowledge of concurrency, memory management, and performance optimization in Go.
• Proven track record of designing and deploying microservice architectures in high-availability, high-throughput environments.
• Solid understanding of message queues, event-driven architectures, and asynchronous processing.
• Strong understanding of microservice architecture and REST/gRPC APIs.
• Strong understanding of networking data transmission protocols (TCP, UDP, WSS, etc.)
• Experience building and deploying cloud-native applications
• Familiarity with containerization technologies (Docker) and orchestration engines (e.g., ECS, Kubernetes).
• Proficiency with message brokers (e.g., Kafka) and distributed systems.
• Knowledge of data storage technologies such as PostgreSQL, Redis, and time-series databases.