Tools engineer állások X. kerületben (adatbázisszakértő)

• Learn data engineering principles
• Learn to design and implement ETL processes and pipelines
• Work with SQL, Python and different programming languages and notebooks
• Learn Power BI report building, Data Bricks and various ETL tools

• Learn Generative AI principles and models
• Learn Large Language Models, Natural language processing
• Work with Different generative AI Tools and uses
• Learn the LLMs, NLP fundamentals, Transformers, and attention mechanism
• Build Custom dataset for LLM, Build your own custom chatbot/AI bot/custom GPT

• Design, build, and maintain robust data pipelines that are scalable, efficient, and meet business needs
• Collaborate with cross-functional teams to understand and translate business requirements into data solutions

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, implement and enhance data solutions for customer organizations Implementation of data integrations (e.g. load data from operative systems like ERP or CRM) Development of data platform / data warehouse in cloud platforms (e.g. data transformation and aggregation) Implementing...

Design and build scalable data pipelines that support AI-enabled digital experiences, personalization, and marketing automation. Leverage AI-driven development and testing tools to increase engineering quality, speed, and reliability. Contribute to ongoing platform modernization efforts across...

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,...

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,...