Python programme állás, munka

• Design and implement automation for storage provisioning, capacity management, and operational workflows using Python, Bash, and IaC tooling
• Drive reduction of manual toil through scripted workflows and self-service enablement

• Turning data science and AI experiments into production-ready, scalable solutions
• Developing and deploying Generative AI solutions including LLMs and Diffusion Models
• Designing and implementing data models and flows including ETL, embedding models and vector databases

• Build-from-zero applications powered by the HawkAI Engine
• Bridge machine learning models and real-time data pipelines into APIs and user interfaces
• Integrate AI-assisted development tools into software architecture and data integrity workflows

• 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

• 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

• Establish data feeds with custodian banks, data vendors, and other service providers
• Support senior leadership, clients, and the broader Data Team in executing analyses and providing data-driven answers to questions
• Fully automate and centralize existing data integration processes

• Delivery on complex projects individually or by leading small delivery teams
• Management of customer relationships alone or in collaboration with a Project Manager
• Support of pre-sales process
• Mentoring of more junior engineers
• Contribution to hiring best-in-class data talent

• Delivery of complex data engineering projects individually or by leading small delivery teams
• Management of customer relationships alone or in collaboration with a Project Manager
• Support of pre-sales process
• Mentoring of more junior engineers
• Contribution to hiring best-in-class data talent

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...

• 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

• Design and build learner models including knowledge tracing and longitudinal approaches
• Shape the data foundation for learner modeling by defining relevant signals and building datasets
• Translate mastery and progression definitions into model targets and evaluation criteria

• Ownership of data models and storage architecture behind AI systems across relational, graph, and retrieval-oriented data
• Building and operating APIs, backend services, and pipelines to keep data current and accessible

• Creation and preparation of 3D assets, environments, and scene layouts for Omniverse and OpenUSD workflows
• Assembly of digital-twin scenes for industrial, facility, product, or enterprise visualization use cases

• Komplex üzleti folyamatok végpontok közötti automatizálása Java és Spring Boot alapokon
• Automatizációs megoldások fejlesztése UI és API szinten Selenium, LeanFT és hasonló eszközök bevonásával
• AI-alapú prototípusok, belső eszközök és automatizációk fejlesztése kontrollált vállalati környezetben

• Development, testing, and maintenance of data pipelines to extract, transform, and load (ETL) data from various sources
• Writing high-quality, maintainable Python code
• Participation in code reviews
• Participation in technical discussions for tool selection and architectural decisions

• 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 (Terraform) and CI/CD

• 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