IT engineer Data & Analytics DevOps

Job description

Continental develops pioneering technologies and services for sustainable and connected mobility of people and their goods. Founded in 1871, the technology company offers safe, efficient, intelligent, and affordable solutions for vehicles, machines, traffic and transportation. In 2023, Continental generated sales of €41.4 billion and currently employs around 200,000 people in 56 countries and markets.  Guided by the vision of being the customer's first choice for material-driven solutions, the ContiTech group sector focuses on development competence and material expertise for products and systems made of rubber, plastics, metal, and fabrics. These can also be equipped with electronic components in order to optimize them functionally for individual services. ContiTech's industrial growth areas are primarily in the areas of energy, agriculture, construction, and surfaces. In addition, ContiTech serves the automotive and transportation industries as well as rail transport. The IT Digital and Data Services Competence Center of ContiTech caters to all the Business Areas in ContiTech and responsible among other on areas of Data & Analytics, Web and Mobile Software Development and AI The team for Data services specializes in all platforms, business applications and products in the domain of data and analytics, covering the entire spectrum including AI, machine learning, data science, data analysis, reporting and dashboarding. • 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. • Qualifications ▪ Degree in Computer Science, Engineering, Information Systems, or a related field. ▪ Minimum 5 years of experience in platform engineering, DevOps, or SRE roles, with a strong focus on automation and infrastructure engineering. ▪ Strong hands-on experience with cloud platforms (Azure preferred), Infrastructure-as-Code (Terraform/Bicep), and CI/CD pipelines. ▪ Experience designing and operating production-grade data platforms and pipeline ecosystems (Scala / Spark environments). ▪ Strong understanding of distributed systems, reliability engineering, and observability practices. ▪ Experience with Databricks platform operations and Spark workload optimization. ▪ Experience integrating build and deployment pipelines (e.g., SBT, github enterprise). ▪ Experience with Power BI service administration and enterprise gateway architectures is a plus. ▪ Strong focus on automation-first approaches with minimal reliance on manual operations. ▪ Ability to work across global teams and collaborat