Data specialist állások, munkák it programozás, fejlesztés területen

• Design of Azure cloud infrastructure to support Databricks and data platform workloads
• Implementation of Azure cloud infrastructure to support Databricks and data platform workloads
• Management of Azure cloud infrastructure to support Databricks and data platform workloads

• Analyze current-state ITIL processes and identify improvement opportunities across the Norlys Tech Hub transformation context
• Support definition and documentation of target-state processes, roles, responsibilities, controls, and governance structures

Performing tasks related to the position....

• Client-facing communication
• Participation in pre-sales discussions
• Collaboration with sales and customer success teams
• Communication with clients' technical teams
• Solution design and delivery
• Design and configuration of data labeling and processing pipelines using Python-based tools

• Act as the link between business stakeholders and technical teams translating business requirements into clear ServiceNow solutions
• Support clients in process analysis optimization and documentation in alignment with ServiceNow best practices

• 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

• Owning a revenue target across data, advanced analytics, and predictive AI
• Leading executive-level client conversations, joining deals early to diagnose the business problem, structure a solution, and build the ROI case that gets the client to sign

• Managing the project lifecycle delivery of Sustainability & Climate Corporate Solutions for the Corporates client segment
• Serving as the dedicated client liaison during each project engagement

• Design, build and deploy LLM-powered pipelines and autonomous agents
• Scope and deliver AI solutions with stakeholders
• Work with frameworks like LangChain
• Set best practices around MLOps and production-grade AI
• Mentor developers
• Contribute to internal knowledge-sharing

• Design, build and deploy LLM-powered pipelines and autonomous agents
• Solve real operational challenges from intelligent automation to advanced retrieval systems
• Work closely with stakeholders to scope and deliver solutions
• Use frameworks like LangChain

• End-to-end AI solution ownership from problem definition through prototype validation and production support
• Partnership with product managers and business stakeholders to translate real-world problems into data science and AI initiatives

• Development and continuous improvement of Information Governance framework
• Definition of governance operating models for customer and business information lifecycle management
• Driving Information Governance maturity improvements

• Ügyfelekkel közvetlen egyeztetés az igények felmérésére és az ügyfél oldali adatplatform célarchitektúrájának megtervezése Microsoft Fabric alapú megoldásokra fókuszálva
• Projekt-előkészítési és értékesítés-támogatási (presales) feladatok vezető szerepű ellátása

• 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

• Design, build and maintain scalable data pipelines and backend services
• Support real-time decisioning, analytics, reporting and data collection
• Translate business/data requirements into appropriate data models and technical solutions
• Manage data transformation, integration and processing

• ML-based Forecasting & Pricing: Lead the development of machine learning models for inventory forecasting and pricing strategies.
• Data Management: Drive data integration, quality, quantification, and enrichment of inventory data.

• Designing, implementing, testing, and optimizing reliable, efficient, and high-quality data pipelines
• Automating the extraction, loading and transformation of data from a wide variety of sources
• Developing solutions for the automated acquisition of data from source systems

• Experience in different data science topics
• Independent delivery of data science projects with e2e product-oriented mindset
• Direct engagement with clients to understand business objectives and translate into technical requirements
• Leading pre-sales technical discussions

• Design and implement enterprise-scale data pipelines and advanced analytics dashboards
• Develop and optimize data ingestion, transformation, and modeling workflows across structured data environments and cloud-based platforms

• Understanding global business strategy and translating on business department/employee level
• Creating the alignment within the organisation for implementing action plans
• Proactive testing of new solutions and proposals to leverage service delivery maturity