Data science állások, munkák programozó, fejlesztő kategóriában

• Define and implement cloud infrastructure and observability tooling - Be a passionate software developer
• Support and develop complex and innovative shared development utilities
• Create and maintain automation processes
• Implement cloud services - Develop holistic software modules

• Develop and maintain web applications featuring interactive 3D visualizations
• Turn product requirements into clear, engaging visual experiences
• Implement 3D scenes, interactions and visualization features
• Create 3D assets suitable for web-based rendering

• Your responsibility: From day one, you'll own your stories and take end-to-end responsibility for your tasks.
• Your team: You'll work in a small team of no more than five full-stack engineers. Like this, our teams are more efficient and can move fast.

• Data pipeline development
• Data integration
• Data warehousing
• Data modelling
• Data quality and governance
• Performance optimization
• Collaboration with data scientists and analysts
• Technology selection
• Security and compliance
• Monitoring and troubleshooting

• Development and maintenance of the C++ application and related scripts
• Work in a Linux environment using GCC and common command-line development tools
• Investigation of issues in existing software, identification of root causes, and implementation of reliable fixes

• Technical leadership and mentoring of data engineers
• Technical oversight for Databricks solutions
• Design and implementation of scalable ETL/ELT pipelines using Databricks, Python/PySpark, SQL, and Delta Lake

• Maintenance and enhancement of an automated market-making application
• Development and maintenance of C++ and python backend applications and services used in brokerage-related systems
• Investigation of issues in existing software, identification of root causes, and implementation of reliable fixes

• Definition and driving of cloud products and platforms evolution
• Collaboration with engineering teams and stakeholders across Deutsche Telekom
• Definition of product vision, strategy, and roadmap for cloud products and platforms
• Understanding of customer needs, market trends, and business priorities

• Develop and implement AI-driven workflows for optical system design
• Combine modeling, simulation, data analytics, and machine learning to enable efficient
• design processes
• Contribute to modern software and toolchains for advanced system development

• Understand the business - Assess and support the business objectives for digital products and services from a Cloud Applications point of view
• Define the architecture - Create structures of distributed systems in close collaboration with other experts

• Understand the business - Assess and support the business objectives for digital products and services from a Cloud Applications point of view
• Define the architecture - Create structures of distributed systems in close collaboration with other experts

Predictive ML: Build models for lead generation, demand forecasting, residual value forecasting, portfolio steering, and fraud detection....

• Develop and integrate AI (Artificial Intelligence) components (LLM agents, RAG pipelines, API integrations) into existing platforms
• Develop software using TypeScript in modern technology stacks (NestJS, Vue 3), including testing and code reviews

• Develop an efficient and reproducible workflow for application-oriented machine learning solutions.
• Be involved in sample preparation and data acquisition in the laboratory for full data ownership

• Planning, design, implementation, and maintenance of Rust components and applications
• Collaboration with the Hungarian Data Science team to build a unified SDK for AI-based models integration into Aether
• Review of requirements and contribution to feature design

• Design and implementation of complex enterprise-grade software solutions
• Definition and evolution of application, data, and integration architectures
• Design and architecture of service-oriented and event-driven systems
• Development of distributed, resilient, and highly available platforms

• Design, optimize, and extend transaction surveillance and data pipeline processes
• Navigate between strategic, system-level architecture and function-level implementation details of surveillance system
• Optimize data architectures and databases for maximum performance and reliability

• Building scalable testing frameworks
• Designing comprehensive test suites covering unit, integration, and acceptance testing
• Collaborating with engineers and data scientists to embed quality practices throughout the development lifecycle

Grow personally as a key player in the global finance team by developing the system landscape, creating data pipelines and BI products that facilitate automation and delivery of complex recurring and ad-hoc tasks across various functions, including global supply chain, sustainability, research...

• Building one governed front door for every lead with validation, de-duplication, consent, and enrichment
• Building AI-native lead qualification models with comprehensive signal analysis and explainable scoring
• Building intelligent lead routing with territory, capacity, availability, and priority data