Python developer állás, munka

• 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

• Active partnership with sales and project managers to estimate, design, develop and deliver solutions
• Continuous communication with domain experts and product owners to understand core business needs and goals to synthesize requirement and quality standards

Development and enhancement of the MSCI Index Development Platform and the IndexMetrics Real-Time application using modern software engineering practices, Python, Azure, and AI-assisted development tools...

• Building AI-assisted development workflows for code understanding, documentation, build triage, and handover preparation
• Implementing and maintaining AI-assisted engineering utilities for repository indexing, code summarization, dependency extraction, log parsing, and documentation generation

• 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

• 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
• Providing technical solutions and implementing new software features collaboratively

• Design, develop, and maintain automated test suites as code using Java
• Create BDD-based automated test scenarios using Cucumber against REST APIs
• Automate API testing for OAuth 2.0 and OpenID Connect (OIDC) authentication and authorization flows using RestAssured or similar tools

• Writing clean, maintainable Python code and automation scripts (bash/shell)
• Building CI/CD pipelines and deployment automation for AI systems
• Creating infrastructure as code and configuration management solutions (terraform)
• Developing APIs, microservices, and event-driven architectures

• Industrialize AI-assisted engineering workflows for Meridian
• Package repeatable patterns supporting codebase intake, dependency extraction, build triage, documentation generation, and technical evidence creation across cloud software work packages

• Learning from senior team members
• Participation in security penetration testing projects including application-level penetration testing (e.g., web application, Android, or iOS Mobile application)
• Participation in infrastructure level security penetration testing
• Participation in Red Teaming

Ownership of detection capabilities end to end from problem framing and data through experimentation to production models and telemetry...

• Design and maintain enterprise-wide data models including conceptual, logical, and physical layers
• Lead data architecture for core platforms and support cross-value-stream data requirements
• Define data standards, naming conventions, and modelling best practices

• Building and operating Kubernetes platforms on Open Telekom Cloud
• Managing Infrastructure as Code with Terraform and Terragrunt
• Implementing GitOps delivery using ArgoCD
• Operating PostgreSQL and Apache Kafka on Kubernetes
• Integrating security controls into CI/CD pipelines

• Strengthening Meridian software handover readiness by combining AI-assisted software engineering with code quality, security validation, dependency analysis, and build evidence generation for complex cloud platform repositories
• Trustworthy validation of large codebases

• 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

• Design and implement pipelines to ingest, clean, and transform data into Data Lakes and Data Warehouses
• Active monitoring and optimization of pipelines for performance and cost
• Configuration of pipeline deployments and management of environment settings using IaC tools and CI/CD

• Lead the design and implementation of scalable data pipelines and Lakehouse architectures
• Act as the design authority
• Solve the hardest technical challenges including optimizing high-load streaming pipelines, debugging complex Spark jobs, and designing generic frameworks

• Development and optimization of large-scale data processing workflows using Apache Spark, PySpark, and SQL
• Building and enhancing multi-stage ETL pipelines with idempotency and failure recovery
• Implementation and configuration of pipeline orchestration using Airflow, Dagster, or Prefect

• Definition and improvement of metrics reflecting product performance, service quality, and operational efficiency
• Analysis of client behavior and service processes to identify trends, bottlenecks, inefficiencies, and drivers of performance

• Design and implement new market links and connectivity tools
• Improve and maintain existing high-load, low-latency C++ applications
• Actively reduce latency to optimize trading performance
• Ensure operational excellence and reliability of systems as they scale