Python programozó diákmunka állások Budapesten (it programozás, fejlesztés)

• Design and maintain enterprise-wide data models including conceptual, logical, and physical layers
• Lead data architecture for core platforms and support cross-value-stream data requirements
• Define data standards, naming conventions, and modelling best practices

• Measuring performance of multi-channel patient recruitment campaigns across clinical trial portfolios
• Optimizing performance of multi-channel patient recruitment campaigns across clinical trial portfolios

• Industrialize AI-assisted engineering workflows for Meridian
• Package repeatable patterns supporting codebase intake, dependency extraction, build triage, documentation generation, and technical evidence creation across cloud software work packages

• Building complex financial analysis utilizing Microsoft Excel, Python, Alteryx, KNIME, Power BI & Tableau
• Participation in significant international transaction projects
• Collecting, researching and analyzing data related to the client’s business operations

• Design and run Kubernetes environments optimized for AI inference, retrieval, experimentation, and agent execution in secure or isolated settings
• Deploy and operate open-source or open-weight model stacks, model gateways, vector databases, and supporting platform components

• Further development of existing optimization components of the airline management system Netline/Crew or Netline Scheduling area
• Implementation and experimentation on new and efficient optimization approaches
• Recording customer requirements for the commissioning of existing optimization components

• Building and operating Kubernetes platforms on Open Telekom Cloud
• Managing Infrastructure as Code with Terraform and Terragrunt
• Implementing GitOps delivery using ArgoCD
• Operating PostgreSQL and Apache Kafka on Kubernetes
• Integrating security controls into CI/CD pipelines

• Building, configuring and maintaining bare metal hosts and Kubernetes clusters to run GPU/AI workloads
• Designing and operating NVIDIA AI related software stack (Slurm, Run AI)
• Providing customized application support for AI related workloads

• Design, deploy, and manage scalable cloud and hybrid infrastructure environments with a primary focus on automation, reliability, and security
• Build and maintain Infrastructure-as-Code solutions using Terraform and other automation tools to provision and manage AWS and on-premises resources

• Design and develop scalable cloud security automation solutions across multi-cloud environments
• Build and maintain platform services using modern engineering practices and a code-first approach
• Own and enhance CI/CD pipelines that enable secure, reliable and efficient delivery

• Data pipeline development
• Data integration
• Data warehousing
• Data modelling
• Data quality and governance
• Performance optimization
• Collaboration with data scientists and analysts
• Technology selection
• Security and compliance
• Monitoring and troubleshooting

• Build and maintain scalable, reliable, and secure environment on AWS using Infrastructure as Code tools
• Oversee the deployment, configuration and management of clusters
• CI/CD pipeline development with designing and managing CI/CD pipelines, Infrastructure as Code, and GitOps toolset and skillset

• Build and maintain scalable cloud infrastructures using modern services and best practices
• Proactive detection, analysis, and fixing of vulnerabilities and performance bottlenecks in cloud environments

• Active partnership with sales and project managers to estimate, design, develop and deliver solutions
• Continuous communication with domain experts and product owners to understand core business needs and goals to synthesize requirement and quality standards

• Design, develop, and implement complex and scalable data solutions on the AWS cloud platform
• Design, build, and optimize data pipelines to ensure efficiency and reliability
• Write clean, efficient, and maintainable SQL and Python code
• Develop and maintain shell scripts to support automation

• Strengthening Meridian software handover readiness by combining AI-assisted software engineering with code quality, security validation, dependency analysis, and build evidence generation for complex cloud platform repositories
• Trustworthy validation of large codebases

Support Meridian technical due diligence and transition readiness by using AI-assisted software engineering methods to understand OpenStack-derived cloud services...

• End-to-end penetration testing engagements across web applications, APIs, cloud environments, binary applications and internal/external infrastructure
• Simulation of real-world attacks to identify security risks before they become threats

• Design and build secure infrastructure foundation for AI-assisted software development
• Operate Kubernetes environments hosting AI engineering tools and services
• Implement GitOps and Infrastructure as Code patterns for provisioning and configuration

• Design, develop, and maintain automated test suites as code using Java
• Create BDD-based automated test scenarios using Cucumber against REST APIs
• Automate API testing for OAuth 2.0 and OpenID Connect (OIDC) authentication and authorization flows using RestAssured or similar tools