Senior Golang Engineer, Data Processing

This is a fully remote position, open to applicants in Canada.

📋 Description

• Design and develop high-performance data-processing services in Go that manage real-time telemetry at an industrial scale.

• Take full ownership of data pipelines from ingestion and transformation through to routing and delivery.

• Enhance throughput, latency, and reliability in systems that must not lose data.

• Create streaming integrations using messaging systems like NATS and MQTT.

• Partner with platform and edge teams to deliver features for both cloud and constrained edge environments.

• Implement observability practices to identify issues before they impact customers.

• Write clean, testable Go code with appropriate error handling.

• Conduct thorough code reviews and elevate engineering standards.

⛳️ Requirements

• Over 5 years of backend engineering experience with strong, hands-on expertise in Go.

• Proven experience in building data pipelines, stream processing, or high-throughput distributed systems.

• Practical experience with Docker and Kubernetes in production settings.

• Comfortable working in Linux/Unix environments on a daily basis.

• Strong understanding of concurrency, performance tuning, and memory management in Go.

• Familiarity with messaging systems such as NATS, Kafka, MQTT, or similar technologies.

• Solid understanding of databases, including time-series or NoSQL solutions.

• Demonstrated history of owning critical production services and successfully resolving issues.

• Experience with industrial protocols such as OPC-UA or MODBUS, or background in IoT/edge computing.

• Knowledge of InfluxDB or TimescaleDB.

• Experience with monitoring tools such as Prometheus, Grafana, or Datadog.

• Experience in cloud-native development on platforms like AWS, GCP, or Azure.

• Must not require visa sponsorship; Litmus does not offer visa sponsorship at this time.

🏝️ Benefits

• Make a tangible impact on the product and the company's trajectory.

• Enjoy ownership and visibility within a growth-stage organization.

• Thrive in a collaborative, curious, and low-ego culture.

• Opportunity to develop infrastructure that powers industrial AI.

• Work on actual customer production systems.

• Collaborate with experienced operators, engineers, and leaders.