Devops állások IV. kerületben (adatbázisszakértő)

• B2C szakmai és technológiai projektek beazonosítása, üzleti igények felmérése
• Vezetői előterjesztések, döntés-előkészítő anyagok, ROI- és hatástanulmányok készítése
• Projektek megtervezése, előkészítési folyamatok koordinálása, ütemezés, erőforrás- és költségtervezés

• Managing and Expanding Data IT team located in different countries of the Region;
• Overseeing the integration of data into the enterprise data warehouse, collaboration with department heads to ensure accurate and relevant reporting data;

Assessment/blueprinting of enhancements and projects providing ensuring solutions meet or exceed business value propositions and meet architectural policies....

• Design and maintain robust, scalable data architectures
• Build and optimize high‑performance data models for analytics
• Partner with business and engineering teams to shape data solutions end‑to‑end
• Lead data integration, transformation, and migration efforts

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...

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,...