Data engineer állások, munkák egyetemi végzettséggel

• Unique opportunity to contribute to the development of the SAP-RPT model family
• Design, develop and manage tools and data pipelines that enable the processing of tabular data at scale

• Architect and build the high-performance backbone of our data platform
• Focus on distributed computing stability and building effective caching strategies for large-scale operations
• Design ETL pipelines and architect resilient caching for complex dependency resolutions

Architect and implement cloud-native data solutions using GCP (BigQuery, Dataflow, Pub/Sub, Dataproc, Cloud Composer, Cloud Storage) Lead the design and development of complex data pipelines and distributed processing frameworks that ensure scalability, performance, and operational reliability...

NEW SOLUTIONS EMERGE WHEN THINKING ISN'T HARD-WIRED. More than 90% of automotive innovations are based on electronics and software. That's why creative freedom and lateral thinking are so important in the pursuit of truly new solutions. Naturally, this includes flexible working models, so that our...

• Build Fullstack Features: Implement user-facing features using modern frameworks and connect them to backend APIs.
• Backend Development: Contribute to Python-based backend services (Django REST or FastAPI), including API endpoints and business logic.

Develop and drive the implementation of Cloud Data Security strategy in alignment with the Product Manager, Tech Lead, and Engineering Manager....

• Architect and build the high-performance backbone of our data platform
• Focus on distributed computing stability and building effective caching strategies for large-scale operations
• Design ETL pipelines and architect resilient caching for complex dependency resolutions

You build and maintain end-to-end ML pipelines using workflow orchestration tools: from data ingestion to distributed training, evaluation, model compilation, and deployment-ready artefacts....

• Architect complex data flow solutions, enabling transparent, versioned, and fully auditable computations
• Design the data layer by developing metadata and data lineage models fused by semantic graphs and numerical data

Conduct field measurement campaigns using Rosenxt measurement technologies....

Planning, project planning, calculation and installation execution planning of electrotechnical systems...

• Contribute to pioneering technical advances to the field of foundation models on structured data, as well as exploringthe benef world models for solving business problems.
• Execute scientific experiments on internal as well as public data.

Lead Data Scientist (f|m|d) | 100% | Hybrid working model | Zurich Switzerland Company Description Welcome to SMG Swiss Marketplace Group! SMG is a pioneering network of online marketplaces and a leading European digital company that simplifies people’s lives with forward-looking products. We...

• Design, develop, and optimize vacuum pumps and compressors to meet product req uirements and ensure compliance with standards and legal requirements.
• Contribute to development projects from concept phase to serial production, collaborating closely with project managers and cross-functional teams.

You teach fundamental knowledge with high practical relevance, e.g. for the topics bias assessment, societal impact, methodology evaluation, and responsible technology, and are responsible for correcting exams....

• Design, build and operate scalable test automation frameworks for enterprise environments
• Drive and consult on test automation strategies for our customers
• Develop and maintain automated test cases (e.g. regression, integration, system and acceptance tests)

• Design Optical network solutions for Data Centers and LAN projects using Corning products
• Create and check Bills of Materials (BOMs) for customer projects
• Support customers and sales teams with technical advice and solution design
• Turn customer requests (RFQs) into clear technical solutions

• You design, build, and manage Kubernetes clusters on AWS EKS with high security and scalability standards for autonomous driving AI/ML workloads.
• Furthermore, you provision and orchestrate large-scale GPU clusters for distributed AI/ML training and experimentation.

You design the reference architecture for the ML platform end-to-end: data ingestion, PB-scale data lake, heterogeneous training clusters, model registry, and deployment-ready artefacts....