Python programme állások XI. kerületben középiskolai végzettséggel

• Co-design and implement QA workflows using statistical diagnostics, validation rules, and anomaly detection techniques
• Apply AI/machine learning tools to identify inconsistencies, missing values, or suspicious patterns in large-scale asset datasets

• NAPI ÜZEMELTETÉSHEZ SZÜKSÉGES FELADATOK ELLÁTÁSA, HIBAJEGYEK KEZELÉSE,
• RENDSZER MONITOROZÁSA, MONITOROZÓ AUTOMATIKÁK RIASZTÁSAINAK FOGADÁSA,
• Részvétel a felmerülő problémák okának kiderítésében,
• Élesítések, telepítések elvégzése,
• Üzemeltetési dokumentációk naprakészen tartása

• Design, build, and deploy production-grade agentic AI and automation solutions that collect, validate, and quality-assure data at scale
• Engineer multi-agent orchestrations, data pipelines, MCP integrations, and API connections that power autonomous, end-to-end data workflows

• Creation of 3D rigs for different types of objects, animals and characters
• Collaboration with the visual effects supervisor and Lead CG to determine the best possible technical and creative approaches
• Delivery of work within established project targets and high quality standards

• Writing reusable, testable, and efficient code mainly in Python
• Delivering great user experience by the development of great user interfaces
• Handling security and data protection professionally and precisely
• Providing technical solutions and implementing new software features collaboratively

Development and enhancement of the MSCI Index Development Platform and the IndexMetrics Real-Time application using modern software engineering practices, Python, Azure, and AI-assisted development tools...

• Lead the design and implementation of scalable data pipelines and Lakehouse architectures
• Act as the design authority
• Solve the hardest technical challenges including optimizing high-load streaming pipelines, debugging complex Spark jobs, and designing generic frameworks

• Design and implement pipelines to ingest, clean, and transform data into Data Lakes and Data Warehouses
• Active monitoring and optimization of pipelines for performance and cost
• Configuration of pipeline deployments and management of environment settings using IaC tools and CI/CD

• Technikai menedzsment és fejlesztés a csapat felhőalapú adatplatformján és adatmodellein Azure Databricks környezetben
• A Data-Driven Project Modelling (DPM) motor fejlesztése és karbantartása DevOps legjobb gyakorlatok szerint