Data science állások, munkák it programozás, fejlesztés területen

• Design and own the Azure Native Data & AI Platform architecture
• Lead Azure Databricks platform implementation and evolution
• Define enterprise data, analytics, ML and AI platform standards and best practices
• Design Lakehouse and Medallion architectures

• Development of dashboards
• Support of data integration
• Analytical investigations
• Identification of trends, risks and opportunities
• Transformation of complex workplace, supplier and operational data into meaningful insight
• Delivery of accurate, insightful and timely reporting

• Support the execution and continuous improvement of the global Business Continuity Management program
• Serve as a key operational point of contact for day-to-day Business Continuity Management activities and the Business Continuity Management platform

• Szoftver fejlesztési és bevezetési projekteken az informatikai rendszerek, alkalmazások előkészítése, igények feltérképezése, teljes körű tervezése, meglévő rendszerek továbbfejlesztése
• Megtervezett rendszerek kiépítésének ellenőrzése, bevezetések szakmai támogatása

• Build and maintain Azure Databricks solutions
• Develop scalable ETL/ELT pipelines
• Implement and optimize Lakehouse solutions
• Develop Spark applications
• Develop reusable data and AI platform components
• Build and maintain MLOps pipelines using Azure Databricks
• Automate platform, data and ML deployments

• Manage and maintain all hierarchical structures within Workday, including but not limited to finance metadata, custom organizations
• Configure Cost Center and Company Hierarchy’s in Workday for non-integrated ERP systems

Az Egészségügyi Ellátási Divízió adott szakterületének üzleti megértése, informatikai támogatása...

• Client-facing communication
• Participation in pre-sales discussions
• Collaboration with sales and customer success teams
• Communication with clients' technical teams
• Design and configuration of data labeling and processing pipelines
• Combination of multiple data labeling components into automated workflows

• Design and build the next generation of the single-security analytical modeling platform using C++23 and Python 3
• Influence the strategic development of analytical services in Aladdin by understanding business processes, identifying bottlenecks, and improving cloud-compute performance

• Crafting innovative solutions through requirements analysis
• Constructing workflow charts
• Drafting precise specifications
• Transforming business requests into actionable development plans
• Creating user stories
• Creating robust acceptance criteria
• Guiding projects from concept to seamless implementation

• Understand business needs 
• Support project delivery 
• Spot opportunities for improvement 
• Be the problem-solver 
• Drive digital adoption 
• Collaborate to create value 
• You have a university degree in: Business Informatics, Information Technology, Software Engineering or similar field.  

• Build, operate, and improve production data pipelines using Python, Airflow, Kubernetes, and related technologies
• Design scalable data pipelines and data models for growing data volumes and processing needs

• A vállalat működéséhez kapcsolódó üzleti és fejlesztési igények feltárása, pontosítása és dokumentálása
• A jelenlegi folyamatok, rendszerhasználat és működési hiányosságok elemzése, fejlesztési javaslatok előkészítése
• Fejlesztési igények üzleti és funkcionális követelménnyé alakítása

• Design and build agentic systems that plan, call tools and automate real business workflows
• Develop LLM-powered applications including RAG pipelines: chunking, embedding, retrieval strategies, evaluation and iteration

• Design, build, review, test, and maintain Ruby on Rails features and services in line with Diligent’s agile engineering practices
• Own technical delivery for projects, epics, and major user stories, including solution design, implementation planning, and execution through to production

• Üzleti és informatikai igények összegyűjtése, elemzése és specifikálása különböző IT projektekben.
• Kapcsolattartás és együttműködés az üzleti területekkel, valamint a fejlesztőcsapattal.
• Funkcionális és nem funkcionális követelmények meghatározása és dokumentálása.

• Design and implement data fabric architecture across heterogeneous data sources and platforms
• Develop scalable ETL/ELT pipelines for batch and real-time data integration
• Integrate structured and unstructured data from databases, APIs, SaaS applications, data lakes, and enterprise systems

• Technical management of a team of 2-3 AI and cloud engineers focused on fast prototyping of AI/ML solutions in AWS cloud
• Mentoring and technical support to junior and medium teammates
• Acting as a trusted advisor to clients
• Development of highly scalable services realizing AI/ML functionalities

• Design, implement, and optimize compiler passes and transformations using LLVM/Clang or GCC
• Build and maintain robust toolchains
• Support new and complex architectures in compiler backends
• Work on architecture-agnostic and IR-level optimizations
• Work on silicon specific optimizations

• Building and optimizing inference pipelines for large-scale model serving
• Working with frameworks like PyTorch, TensorRT, and vLLM to deploy models efficiently
• Implementing and optimizing ML models using techniques such as quantization, kernel fusion, and efficient batching