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• Building, operating and improving production data pipelines using Python, Airflow, Kubernetes and related technologies
• Designing scalable data pipelines and data models for growing data volumes and processing needs

• Configuration of the P&P platform end to end, across both frontend and backend
• Tuning and optimization of forecast and attribution models to match client data and business logic
• Writing custom business logic in SQL, Python, or Go where standard configuration isn’t enough

• Facilitation of discovery workshops with German-speaking clients to capture pricing and promotions requirements
• Documentation of business and technical specifications based on workshop outcomes
• Translation of business needs into functional configuration requirements for the solution team

Agentic AI development: Design and implement autonomous and semi-autonomous AI workflows, including planning, task execution, tool integration, context management, and fault recovery....

• Producing high quality code for the full technological stack from database to UI
• Assisting with troubleshooting basic issues and improving application performance
• Documenting and demonstrating solutions with a focus on security and performance

• 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

• 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

Review business requirements and ensure alignment with end-to-end customer journeys, translating needs into user stories, technical specifications and architecture designs....

• 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

• Magas szintű technikai és üzleti tanácsadás ügyfelek számára az Atlassian termékekkel és saját fejlesztésű megoldásokkal kapcsolatban
• Ügyfelek üzleti és IT folyamatainak felmérése
• Komplex megoldások tervezése, bevezetése és minőségbiztosítása

• Implementation and maintenance of large-scale data pipelines and the Azure/Databricks data platform
• Building robust, scalable pipelines using Azure Databricks (PySpark / SQL)
• Design and enforcement of data architecture standards including Delta Lake / Lakehouse architecture and data modeling

EZEK LESZNEK A FELADATAID • MES fejlesztő kolléga munkájának támogatása • MES funkciók fejlesztésében való segítségnyújtás • Gyártósori adatok elemzésében való részvétel ...

• 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
• Maintaining coding standards, version control practices, and agile routines

• Setup and maintenance of IT cloud infrastructure for multiple products
• Setup and maintenance of the automated build/deployment jobs
• Maintenance of various support tools and utilities
• Monitoring application performance and resource planning

• Writing production-quality, well-tested scraper code in Python
• Learning the architecture of the collection platform including scrapers, proxy layer, queues and enrichment API
• Debugging issues across multiple components using logging, monitoring and alerting tools

• Operate, govern, secure, and continuously improve the Azure Databricks platform, ensuring reliability, scalability, security, and cost efficiency.
• Manage Databricks workspaces, environments, account-level settings, identities, and platform access controls.

• Writing reusable, testable, and efficient code mainly in Python
• Mastering the integration of user-facing elements developed by front-end developers with server side logic
• Integration of data storage solutions
• Handling security and data protection professionally and precisely

• Writing reusable, testable, and efficient code mainly in Python
• Mastering the integration of user-facing elements developed by front-end developers with server side logic
• Integration of data storage solutions
• Handling security and data protection professionally and precisely

• Writing reusable, testable, and efficient code mainly in Python
• Delivering great user experience by the development of great user interfaces
• Handling security and data protection professionally and precisely
• Collaborative work to provide technical solutions and implement new software features

• Ownership of data engineering features, architecture, and code quality
• Design, implementation, and maintenance of Databricks-based data pipelines and workflows
• Building and optimization of ETL/ELT processes using Apache Spark on Databricks