Data engineer állás, munka

• az általunk fejlesztett informatikai rendszerben kezelt üzleti folyamatokhoz kapcsolódó új üzleti igények felmérése, megrendelővel, külső és belső stakeholderekkel történő egyeztetetése
• az üzleti folyamatok felhasználói által támasztott fejlesztési igények összehangolása

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...

Design and implement security architecture for Azure Databricks platforms Enforce Role-Based Access Control (RBAC) across Azure and Databricks environments Integrate security into DevSecOps pipelines, ensuring automated security controls and policy enforcement Manage and secure Azure resources,...

Design & implement AI/ML solutions Build end-to-end ML/AI pipelines: data ingestion, preprocessing, feature engineering, model training, evaluation, deployment and monitoring Develop AI-powered applications and services using Python and modern ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn)...

• Termékfejlesztéssel kapcsolatos üzleti igények, visszajelzések gyűjtése (kapcsolódó interjúk, UAT-ok, megbeszélések szervezése és vezetése)
• Részvétel az üzleti megoldások tervezésében

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,...

Architect, build and maintain backend services and APIs using Python and web frameworks such as Flask or Django (or comparable) Design and implement RESTful APIs / microservices, ensuring clean, maintainable, and efficient code, adhering to best practices (coding standards, documentation, testing)...

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,...

Design, write and execute comprehensive test plans, test cases and test scripts to validate ETL/data‑pipeline processes, data transformations, and data integrity (source‑to‑target, cross‑reference, reconciliation). Validate data extraction, transformation and loading processes for accuracy,...