Data Platform Engineer - Real-Time Streaming

About the role

A Data Platform Engineer is needed to deploy, maintain and expand a real-time data streaming platform that delivers live insight into machine performance. The engineer will onboard new data sources, keep the platform reliable and observable, and build self-service capabilities in Azure so teams can onboard faster. The role suits someone comfortable with Kubernetes, Python, Azure and high-throughput, low-latency data systems.

Key responsibilities

• Deploy, operate and maintain a real-time data streaming application delivering machine performance insights.
• Onboard new data sources, including additional signals from existing machines and newly connected machines.
• Manage the platform lifecycle, including upgrades, patching, capacity planning and deprecations.
• Improve logging, monitoring, alerting and usage measurement, mainly using Grafana.
• Manage role-based permissions and platform access controls.
• Build self-service capabilities, including automated source onboarding through Azure DevOps pipelines.
• Troubleshoot pipeline failures, data quality problems, latency and other data-related issues.
• Automate repetitive operational work with Python scripts and Infrastructure as Code.
• Create and maintain technical documentation, runbooks and onboarding guides.
• Partner with stakeholders to understand data needs and communicate platform status.

Required profile

• Strong Python skills for scripting, automation and data tooling.
• Hands-on experience with Git and version control.
• Production experience running workloads on Kubernetes.
• Experience building dashboards and alerts in Grafana.
• Hands-on Azure cloud experience.
• Experience with Azure DevOps, including pipelines, repositories and release management.
• Experience with high-throughput data and low-latency streaming systems.
• Strong understanding of monitoring, logging and observability, and excellent debugging and troubleshooting skills.
• Strong technical writing and clear English communication; able to work independently in a client-facing environment.

Required skills

• Python, Kubernetes, Azure, Azure DevOps, Grafana, Git
• Preferred: Docker, Terraform, Linux, InfluxDB or other time-series databases