E learning állások Budapesten (it programozás, fejlesztés)

• Delivery on complex data engineering projects across industries
• Leading small delivery teams
• Managing customer relationships alone or with a Project Manager
• Mentoring more junior engineers
• Evaluating the quality of junior engineers' work
• Contributing to hiring best-in-class data engineers

Understanding clients’ mid-term strategies and managing executive relationships with their business and IT leaders...

• Contribution to Customer Platform team
• Delivery of high-quality NodeJS, TypeScript and React code with simplicity, performance, and scalability
• Design and implementation of client and database-related application features

• Technical consultation and client education
• Creation of feasible delivery plans for on-time, on-budget, and high-quality project implementations
• Design and implementation of high-performing, maintainable, and secure software aligned with industry best practices and company capabilities

• Owning the quality architecture for the Scoring engine
• Prioritizing test strategies based on real-world risk
• Standardizing reusable patterns for the repository
• Building reliable automated coverage across UI, API, and deep service layers
• Operating as a power user of AI-first IDEs

• Design and configure Master Batch Records within Rockwell PharmaSuite
• Translate manufacturing process requirements into compliant MES design solutions
• Ensure adherence to global templates, design principles, and regulatory requirements

• Technical leadership of manufacturing execution solutions on Siemens Opcenter Execution Process Enterprise (MES)
• Ownership of middleware architecture and integration layer using Opcenter Connect MOM
• Definition and governance of technical standards, coding guidelines, and architecture decision records

• Build and maintain SQL queries and reports that track bookings, pipeline coverage, and conversion
• Monitor CRM data quality to resolve issues at the source
• Analyze pipeline trends and support the weekly forecasting review cadence with clean, accurate data

• 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

• Training and fine-tuning models against curated datasets
• Running systematic hyperparameter and architecture experiments
• Building and maintaining evaluation suites
• Analyzing model failures and translating findings into dataset or training improvements

• Executing system data maintenance and administrative activities in Cornerstone and relevant learning management systems
• Providing non-systems related learning process support

• Building and maintaining dataset ingestion, cleaning, and versioning pipelines
• Designing and operating labeling workflows including quality control and inter-annotator agreement tracking
• Owning dataset testing including coverage analysis, class balance, leakage detection, and dataset documentation

• Leading and mentoring a team of ML engineers
• Owning model quality end-to-end from experimentation to production-ready artifact
• Conducting regular 1-on-1s for career development and feedback
• Removing blockers and ensuring team well-being

• Improvement of repetitive processes
• Organization, cleaning and analysis of data
• Automation of everyday tools and processes
• Experimentation with AI tools, chatbots and workflows
• Troubleshooting and operational task support
• Data verification and process compliance

• Development of advanced AI solutions
• Collaboration across divisions to design, develop, and deploy machine learning models and AI applications
• Working with state-of-the-art AI technologies including generative AI, natural language processing, and computer vision

• Payroll data oversight across global operations
• Data system development for payroll data management processes
• Development and support of global payroll data management standards
• Management of data integrations and analysis
• Process mentorship for local teams on data hygiene practices

• Experience in different data science topics
• Independent delivery of data science projects
• Engagement with clients to understand business objectives and translate them into technical requirements
• Leading pre-sales technical discussions

• Development and execution of change plans informed by change impacts, stakeholder needs and organizational readiness
• Application and improvement of change management framework and tools drawing on established approaches and Deloitte’s internal practices

• Management and development of a team of 0 to 1 direct reports
• Support of business migration and transition into core company ERPs such as SAP S/4 Hana and E1 with emphasis on manufacturing module migration

• SAP ABAP development including ABAP OO and/or ABAP Cloud
• Assistance with implementing and maintaining SAP software solutions
• Collaboration on the implementation of cloud-based SAP technologies
• Active communication in international projects