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• 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

• 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

• Configuration of the P&P platform end to end across 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 for non-standard configuration

• Manual and automated testing across iOS and Android platforms
• Collaboration with developers, designers, product owners, and fellow QA engineers
• Definition and refinement of test strategies for new functionality and release cycles

• Tackling complex technical challenges focused on scalability, reliability, and speed
• Maintaining a high-performance infrastructure that processes millions of events with low latency
• Collaborating with Data Scientists and Engineers to design and implement cutting-edge feature topologies

• 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

• 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

• fontos szerep a szoftverfejlesztő csapat munkájában,
• hozzájárulás az IT rendszerek továbbfejlesztési projektjeihez,
• aktív részvétel a cég egyik core rendszerének továbbfejlesztésében,
• specifikáció alapján történő fejlesztés,
• részfeladatok önálló megvalósítása, dokumentálása.

• 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

• 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

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• 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 such as logs, monitoring, gathering user feedback
• Monitoring application performance and resource planning

• Board reporting management
• Cross-functional project management
• Process adherence tracking and improvement
• Contract and spend audits and annual planning for vendor contracts
• Business case building for new product investments
• Process automation leadership

• Demo development and content creation
• Support of development projects
• Creation of demo concepts and AI-centric tools based on guidance, customer needs, and platform capabilities
• Support of the development and implementation of demos showcasing product value

• Design and own secure, scalable services
• Guide technical decisions and evaluate trade-offs including AI-driven components
• Leverage AI tools to accelerate coding, debugging, testing, and prototyping

• 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

• Real-time decision making with machine learning for risk assessments
• Ownership of risk infrastructure for Instant ACH in the US market
• Cross-functional collaboration with software engineers, data analysts, and data scientists

• 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

• 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