Lead Azure DevOps

O projekcie: N-iX is looking for a Lead Azure DevOps for one of our clients. The Cloud Engineer role focuses on the design, implementation, and maintenance of an Azure-based cloud infrastructure. This infrastructure is critical for powering connected safety systems, handling secure data ingestion from mobile and embedded devices, and managing scalable storage for telemetry and crash data. The position involves providing reliable notification services for emergency contacts and collaborating with mobile, embedded, and algorithm teams to ensure robust integrations. Additionally, the role supports the deployment of machine learning models for crash detection while maintaining alignment with cybersecurity and data privacy standards. Wymagania: - Experience: At least 5 years of experience in cloud engineering, with a preference for Microsoft Azure - Technical Knowledge: Strong understanding of cloud-native services, serverless architecture, API development, and data pipelines - Security & Compliance: Familiarity with security best practices, including encryption, identity management, and regulatory compliance - Scripting & Automation: Proficiency in scripting and automation tools such as PowerShell, Python, Terraform, or Bicep - Monitoring: Experience using monitoring tools like Azure Monitor, Application Insights, or Prometheus - Tech Stack Proficiency: Familiarity with Azure-specific tools, including Functions, API Management, Event Grid, IoT Hub, Blob Storage, Cosmos DB, and PostgreSQL. Codzienne zadania: - Architecture & Design: Design and implement scalable Azure cloud architecture for telemetry ingestion, user data management, and crash event processing - API Development: Develop and maintain RESTful APIs for the integration of mobile apps and BLE-enabled devices - Database Management: Optimize database design and performance to ensure scalability for telemetry and event workloads - Notification Workflows: Build and manage SMS, email, and push notification workflows triggered by crash events - ML Support: Support the deployment and versioning of machine learning models used for crash detection - Automation & DevOps: Implement CI/CD pipelines for cloud services and infrastructure using Azure DevOps - Optimization: Monitor and optimize cloud resource usage, costs, and overall performance to ensure system reliability under real-world conditions - Compliance: Implement infrastructure and workflows that align with cybersecurity and data privacy standards, such as GDPR and ISO/IEC 27001