Backend Engineer — Data Pipeline

Role overview Build and run backend systems that move inspection data from field devices into processing, storage, analysis, and reporting. The work centers on reliable, low-latency handling of high-volume imagery, point clouds, and sensor telemetry, including when connections or uploads are unreliable.

Responsibilities - Design and operate asynchronous, event-driven ingestion and processing pipelines. - Build services that handle intermittent connectivity, incomplete uploads, and varied field devices. - Improve cloud object storage approaches for large images, video, and point cloud files. - Create queues and worker systems that can absorb spikes in inspection workloads. - Add checks for data quality and completeness throughout the pipeline. - Define and document data contracts between devices, pipelines, and downstream services.

Requirements - At least three years of backend engineering focused on data movement or processing at scale. - Strong Python or Node.js skills for pipeline and worker services. - Experience with message queues or streaming systems such as RabbitMQ, SQS, or Kafka. - Understanding of cloud object storage patterns, such as S3, Azure Blob, or GCS. - Production experience with pipelines for large binary files. - Ability to monitor pipeline health through structured logs, metrics, and alerts.

Benefits and work setup Flexible and remote arrangements are available anywhere in Australia. There are offices in Melbourne and Sydney, and occasional site visits are part of the role.