Top Tech Jobs & Startup Jobs

Responsible for operating ESX hypervisors and supporting complex environments, requiring teamwork and knowledge sharing, with a focus on urgency in incidents.

The Pricing Manager develops pricing strategies, collaborates on pricing models, and advises project teams in contract negotiations to optimize pricing structures for IT contracts.

The Cloud Engineer is responsible for managing Azure environments, implementing cloud services, troubleshooting issues, and ensuring security and compliance while interacting with vendors.

The Data Scientist will analyze data, build machine learning models, design data pipelines, and collaborate with teams to provide insights and solutions.

Design and implement a SUSE-based virtualization platform, establish capacity planning, integrate LINSTOR, and automate infrastructure provisioning with Terraform and Ansible.

Implement, configure, and optimize SAP Project Systems (PS) and Controlling (CO) modules. Design WBS, networks, budgeting, planning, and cost objects. Configure cost centers, profit centers, internal orders, product costing, ABC, and profitability analysis. Manage incidents and changes, provide end-user and project team support, gather requirements, and ensure system quality and business compliance.

Lead platform architecture and 3rd-level operations for Linux and Kubernetes-based platforms. Manage capacity, reliability, automation (Ansible/AWX), observability (Wazuh, Prometheus/Grafana), storage (MinIO, PostgreSQL), networking (NSX-T), audits/compliance, PoCs (Oracle, Cognos), migrations (DB2→PostgreSQL), cross-team incident response, and platform enablement.

The Application Administrator role entails managing Middleware Applications, deploying infrastructure, troubleshooting SSL/TLS, and implementing CI/CD processes within various OS environments.

As an Enterprise Architect, define IT architecture, manage C-level relationships, analyze IT landscapes, and drive cloud service adoption for customers.

Support AI project teams in improving data processing and machine learning pipelines, optimize data solutions, maintain applications, and implement internal process improvements.