E learning állások XXIII. kerületben (it programozás, fejlesztés)

• Development of high-availability, high-prestige enterprise portals and applications
• Participation in system integration projects in both international and domestic markets
• Use of the following technology stack: Java 17+, Spring Boot, J2EE, SQL, Maven, REST, JSON

• Joining junior team assisting with latest projects
• Learning skillset necessary to contribute including working with source code and applying development processes
• Attending online brainstorming sessions regularly
• Learning best practices and key technologies to quickly become productive

• Design, build, and maintain large-scale distributed data systems
• Develop data processing pipelines using technologies such as Spark and streaming solutions
• Work on systems that evaluate and ensure the quality and integrity of large-scale knowledge graphs

• Maintaining and evolving data structures
• Building new ETL flows and maintaining or improving existing ones
• Designing new data structures and data modelling concepts
• Ensuring data quality by verifying data consistency and accuracy
• Creating data validation methods

• Maintaining and evolving data structures
• Building new ETL flows and maintaining or improving existing ones
• Designing new data structures and data modelling concepts
• Ensuring data quality by verifying data consistency and accuracy
• Creating data validation methods

• Writing and maintaining clean, high-quality, and efficient code that aligns with project specifications using AI tools daily to accelerate delivery
• Executing comprehensive testing and seamless deployment of programs and systems

• Development of infrastructure providing insights into operational cost and risk associated with Wise product ownership
• Enhancement of product to reduce Wise's cost for customers and enable smoother experience when additional information is required

• Assistance in developing AI-powered workflows using large language models such as Claude, GPT, and related technologies
• Support for implementation, testing, and maintenance of workflow automation solutions

• Managing day-to-day operations of Databricks data pipelines, including monitoring, troubleshooting, and performance tuning
• Maintaining Delta Lake data layers (bronze / silver / gold), ensuring data availability, consistency, and smooth pipeline execution

• Leading a data engineering team comprising 5-6 consultants
• Overseeing project delivery
• Managing and mentoring the team
• Ensuring successful execution of data engineering projects
• Ensuring successful execution of ML/MLOps projects
• Ensuring successful execution of cloud migration projects

• Architect and lead the development of large-scale ML systems and model pipelines
• Introduce new ML systems such as traffic sign detection, building facade detection, and other computer vision-based solutions
• Define and drive the ML technical roadmap in alignment with company objectives

• Ensure the quality of data across various domains (Security, Portfolio, Counterparty, Ratings, Benchmark, Analytics, Pricing) and within relevant systems.
• Perform assigned daily/monthly processes, escalating issues or determining solutions to remove obstacles for the team.

• Establish data feeds with custodian banks, data vendors, and other service providers
• Support senior leadership, clients, and the broader Data Team in executing analyses and providing data-driven answers to questions
• Fully automate and centralize existing data integration processes

• Build and maintain simulation environments for mobile robotic perception and navigation
• Develop and integrate robotic behaviours and learning pipelines for reinforcement learning and motion planning in complex outdoor environments

Own end-to-end design projects, delivering comprehensive solutions from user requirements and information architecture to task flows, wireframes, and high-fidelity, production-ready interfaces....

• 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

• Learning the Gaming System and underlying business model/processes
• Providing high quality 3rd line technical support for iGaming System to Customer Support Team, Central Gaming, Partners and Engineers
• Participating in regular configurations of iGaming System

• Learning existing system architecture, codebase, tools, and development practices
• Validating existing technical documentation and flagging any gaps or outdated content
• Highlighting blockers to knowledge transfer such as missing info, unclear logic, inaccessible systems

Leading product discovery, definition, and experience-design activities for complex digital systems in regulated industries like energy, financial services or healthcare...

• Leading a data engineering team comprising 5-6 consultants
• Overseeing project delivery
• Managing and mentoring the team
• Ensuring successful execution of data engineering projects
• Ensuring successful execution of ML and MLOps projects
• Ensuring successful execution of cloud migration projects