Data science állások, munkák Budapesten

• Development of web applications in a team using the newest technologies
• Implementation of new functionalities in backend and frontend
• Design and estimation of user stories
• Participation in system design
• Design of user interfaces and functions as planned
• Participation in product roadmap design

• Providing exceptional support throughout the customer lifecycle
• Handling administration
• Order management
• Quotations
• Master data maintenance
• Collaborating with cross-functional teams to deliver outstanding service
• Maintaining the highest standards of accuracy and professionalism

• Data ingestion processes from various sources into the Data Lake
• Design, development and optimization of complex data pipelines for reliable data flow
• Build, development and maintenance of frameworks facilitating construction of data pipelines

• Design, build, and operate enterprise-grade Agentic AI platforms
• Own architecture and delivery
• Mentor engineers
• Partner closely with client and internal teams
• Run secure AI environments at scale under strict regulatory and security requirements
• Architect Zero-Trust environments for LLM-based solutions

• Build and maintain dataset ingestion, cleaning, and versioning pipelines
• Design and operate labeling workflows including quality control and inter-annotator agreement tracking
• Own dataset testing including coverage analysis, class balance, leakage detection, and dataset documentation

• Support the development and evolution of the ERP target picture and ERP strategy for T-Systems
• Evaluate and assess complex SAP system landscapes with focus on consolidation, integration, harmonization, and retirement decisions

Support of routine daily activities for system design, build, testing, validation, maintenance, and ongoing support of all network infrastructure components...

• Design and implement modern data architectures and lakehouse solutions
• Provide technical leadership throughout the project lifecycle
• Collaborate with business stakeholders
• Create effort estimations
• Provide technical expertise during the pre-sales phase
• Mentor 3-6 person project teams

• 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, develop, and implement complex, scalable Lakehouse solutions on the Databricks platform across major cloud environments (Azure, AWS, or GCP)
• Design, build, and optimize modular data pipelines using Delta Lake to ensure data efficiency, reliability, and quality

• Komplex szakmai kihívást jelentő üzleti és informatikai tanácsadási projektek tervezése
• Komplex szakmai kihívást jelentő üzleti és informatikai tanácsadási projektek megvalósítása
• Projektek szakmai irányítása
• Projektmenedzsment feladatok ellátása
• Üzleti elemzés fókusz

• Design, planning, build, and in-life support of IP-based data networks and services
• Design, planning, and build of Data Centre customer connectivity for Managed Services and Telehousing
• Capacity planning of Data Centre and DCN infrastructure

• Training and fine-tuning models against curated datasets
• Running systematic hyperparameter and architecture experiments
• Building and maintaining evaluation suites including regression tests for model behavior and benchmark tracking

• Management of customer orders throughout the order fulfillment lifecycle
• Processing of customer orders, order changes and customer master data requests using ERP and CRM systems
• Monitoring of open orders and proactive communication of updates to customers and internal stakeholders

• Definition of product vision, strategy, and roadmap for cloud products and platforms
• Understanding of customer needs, market trends, and business priorities
• Translation of complex technical challenges into clear product requirements and actionable roadmaps

• 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

• 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

• Understanding and aligning with business needs, identifying related data requirements
• Participating in technical pre-sales activities, including effort estimation, and proposal creation
• Architecting and planning robust data models and modern data platforms

• Development of RTEMS or Linux applications including subsystem command and data handling
• Low-level hardware control
• Automation
• Custom interfaces
• Communication software for space systems and ground support equipment

• Mapping and analyzing business needs and processes to support the development of digital products and data-driven solutions
• Creating specifications for IT development projects, especially for digital platforms and data-centric features such as user stories and use cases