ContiTech USA, Inc. is hiring an IT engineer Data & Analytics DevOps

Job Description ▪ Design, build, and operate a stable, scalable, and secure data platform infrastructure on Azure, including Databricks, CI/CD systems, and Power BI integration. ▪ Take ownership of platform infrastructure, deployment automation, and reliability engineering by reducing manual operations through automation and engineering solutions. ▪ Enable and continuously improve the reliable execution of data pipelines by implementing observability, monitoring, and automated recovery mechanisms. ▪ Build and evolve Infrastructure-as-Code-based platform provisioning and configuration management. ▪ Collaborate with software engineers, ML engineers, and architects to ensure platform capabilities align with development and architectural standards. Main Tasks Platform Engineering & Infrastructure ▪ Design, build, and operate Azure-based platform infrastructure using Infrastructure-as-Code (Terraform). ▪ Automate provisioning, configuration, and scaling of platform components (AKS, Key Vault, Monitor, Storage). ▪ Automate and manage Databricks workspace configuration, access control, and cluster policies. ▪ Define and enforce platform standards for cluster usage, performance, and cost optimization. CI/CD & Automation ▪ Design and implement CI/CD pipelines for Scala-based data applications. ▪ Automate build, packaging, and deployment processes (e.g., SBT, github enterprise). ▪ Enforce DevSecOps practices, including secure pipeline design and infrastructure governance. Reliability Engineering & Observability ▪ Implement observability for data pipelines and platform components (logging, metrics, alerting), using grafana. ▪ Diagnose failures and implement long-term reliability improvements, including root cause analysis and post-incident remediation. ▪ Define and implement reliability engineering practices, including SLIs/SLOs, incident response, and automated recovery mechanisms. ▪ Monitor Spark workloads using logs, metrics, and performance diagnostics. Data Platform Enablement ▪ Enable reliable runtime execution of production data pipelines and ensure SLA adherence. ▪ Collaborate with engineers to resolve performance bottlenecks and deployment issues. ▪ Support environment transitions, and platform lifecycle processes. Power BI Platform Integration ▪ Engineer and automate Power BI service configuration, workspace management, and monitoring. ▪ Design and operate enterprise gateway infrastructure for hybrid data integration scenarios. ▪ Troubleshoot and continuously improve reliability of dataset refresh and hybrid integration pipelines. Governance & Security ▪ Implement and enforce platform governance standards (RBAC, tagging, audit logging). ▪ Design secure secrets and credential management using Azure Key Vault, managed identities, and federated identity credentials. ▪ Automate compliance checks and support platform audits across Azure, Databricks, and Power BI environments. Platform Optimization ▪ Optimize resource utilization, scalability, and cost-efficiency across platform components. ▪ Provide transparency into platform usage, cost drivers, and optimization opportunities.