Data engineer állás, munka

Designing and developing proof of concepts (PoCs) and demonstrating the solution to internal customers on a tight schedule Utilize GenAI no code, low code, and SDKs to build robust GenAI agents that automate business processes to build PoC Take GenAI and Agentic AI solutions from concept to...

• AI-alapú termékeink és backend rendszereink fejlesztése, karbantartása
• API-k (FastAPI, Django REST) tervezése és implementálása
• Adatbázis-struktúrák és architektúrák kialakítása (PostgreSQL, ORM-ek)
• Adatbázis-tervezés és optimalizálás (SQL / NoSQL)

Design, implement, and manage Azure cloud infrastructure to support Databricks and data platform workloads Build and maintain Azure resources including Resource Groups, VNets, Key Vaults, Storage Accounts, and Azure Active Directory (AAD) integrations Implement Infrastructure as Code (IaC) using...

Implement and maintain large‑scale data pipelines and the Azure/Databricks data platform in close collaboration with the Architect, contributing to design discussions and proposals. Build robust, scalable pipelines using Azure Databricks (PySpark / SQL), integrating data ingestion, processing,...

Implement and maintain large‑scale data pipelines and the Azure/Databricks data platform in close collaboration with the Architect, contributing to design discussions and proposals. Build robust, scalable pipelines using Azure Databricks (PySpark / SQL), integrating data ingestion, processing,...

Take ownership of technical challenges, bringing curiosity and resourcefulness to ambiguous problems. Define and drive the development of complex features ensuring scalability, reliability, and security. Translate business requirements into clear technical plans, communicating risk/impact crisply....

Translating business needs into scalable AI solutions Developing enterprise-grade AI solutions Working effectively in a collaborative, multi-disciplinary, and global team environment...

Programming in languages relevant to AI (e.g., Python, Java) Using modern AI/ML frameworks and platforms (e.g., TensorFlow, PyTorch, Oracle Cloud AI services) Enterprise software development including REST APIs, microservices, and cloud-native architectures Translating business needs into scalable...