Senior data analyst állások, munkák Budapesten

• Lead the HSE relevant Enablon developments and ensure a proper support for the users as an HSE product owner.
• Define, monitor and continuously improve corporate HSE KPIs and leading and lagging indicators
• Develop and maintain dashboards and reports to support management decision-making

Design, develop, test, document, and deploy high quality Salesforce solutions leveraging the latest capabilities of the Einstein 1 Platform, Lightning Web Components, and modern Apex patterns...

• Design and build scalable, reusable frameworks and services for data ingestion, transformation, and processing
• Develop and maintain the platform’s core capabilities such as orchestration, data quality validation, and schema management tools

• Fejlesztés, karbantartás és támogatás felhőalapú adatműveleti infrastruktúrán és termelési adatcsatornákon
• Azure-alapú adat szolgáltatások és Databricks munkaterhelések tervezése, megvalósítása, működtetése és optimalizálása

Performing tasks related to the position....

• 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

• Business and system analysis throughout the full feature lifecycle
• Analysis and mapping of processes across the trading stack including accounts, instruments, liquidity and execution, custody, settlement, and reconciliation

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

• 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

• 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

• Design end‑to‑end application architectures aligned with enterprise architecture principles, standards, and strategic directions.
• Translate business requirements into robust, scalable and compliant solution designs covering applications, integrations, and supporting technologies.

• 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

• 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

• 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

• A magyarországi éves értékesítési, regisztrációs és piaci részesedési célok megvalósítása.
• Az értékesítési stratégia, az éves üzleti terv és az akciótervek kidolgozása és végrehajtása.

• 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

• Making collection calls to customers
• Emailing or faxing invoices
• Getting hard copies of invoices mailed out to customers as per their requests
• Understanding all aspects of cash allocation in accordance with customer remittances including deep validation experience and reporting to business

• 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

• 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

• 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