Python programmer állás, munka

• Working with cutting edge technology enabling Cloud Journey
• Managing Infrastructure as Code for parts of Core Platform Layer including Kubernetes Clusters, Message Broker backends, Infrastructure tooling

• 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

• 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

• Software release delivery on schedule with defined scope and quality
• Transition to continuous delivery
• Reliable operation of CI/CD pipelines
• Improvement of CI/CD pipeline efficiency
• Contribution to test strategy
• Coordination of test strategy execution
• Development of test frameworks and automation tools

• 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

• CI/CD-folyamatok tervezése, felépítése és üzemeltetése (Azure DevOps, GitLab CI, GitHub Actions vagy Jenkins)
• Infrastruktúra kezelése kód formájában (Terraform, Bicep/ARM, Ansible)
• Konténeres környezetek felépítése és üzemeltetése (Docker, Kubernetes / AKS)

• Search, collect, consolidate, and validate financial and non-financial data across departments and systems
• Design, build, maintain, and automate dashboards and underlying data pipelines to provide timely, accurate insights to stakeholders

• Kapcsolattartás az ügyfelekkel, igények felmérése és tanácsadás
• Azure Function App fejlesztés
• Dokumentálás
• Programozás Pythonban
• Azure infrastruktúra tervezés és karbantartás
• Rendszeres ellenőrzés, frissítés és teljesítmény optimalizálás Azure környezetben
• Fejlesztések tervezésében aktív részvétel

• Co-design and implement QA workflows using statistical diagnostics, validation rules, and anomaly detection techniques
• Apply AI/machine learning tools to identify inconsistencies, missing values, or suspicious patterns in large-scale asset datasets

• Design, development, and optimization of core ML models, especially in Computer Vision and Deep Learning
• Development of efficient, scalable training and inference pipelines
• Mentoring junior ML engineers, reviewing code and sharing best practices

• 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

• 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

• Definition and development of system-level tests for high-end embedded computing systems
• Automation of test execution and evaluation through scripting in a CI environment
• Increase of test coverage by extending functional examples into comprehensive test suites

Performing tasks related to the position....

• 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

• Design and build learner models including knowledge tracing and longitudinal approaches
• Shape the data foundation for learner modeling by defining relevant signals and building datasets
• Translate mastery and progression definitions into model targets and evaluation criteria

• Ownership of data models and storage architecture behind AI systems across relational, graph, and retrieval-oriented data
• Building and operating APIs, backend services, and pipelines to keep data current and accessible

• Building end-to-end web solutions from UI to backend
• Leading and contributing to development efforts across the full stack
• Design and implementation of web applications using modern frameworks and best practices
• Translation of business and user needs into intuitive, scalable technical solutions

• Native Swift/iOS application development
• User interface and function design as planned
• Requirements gathering participation
• Project and technical planning participation
• Unit and UI test writing
• Developer testing participation
• Continuous learning

• Development and deployment of AI-powered applications using modern software engineering practices
• Integration of Large Language Models into business solutions
• Building scalable backend services using Python or Node.js
• Development of intuitive user interfaces with React or Angular