Python programmer állások, munkák adatbázisszakértő kategóriában

• Partner with internal teams and model researchers to evaluate high-value use cases and understand their business context.
• Analyze use cases across the organization and advise on how to make them work effectively with our tabular foundation models.

• Collect, process, and analyze large and complex data sets.
• Support the development and implementation of data analytics solutions.
• Prepare presentations, reports, and visualizations to effectively communicate data findings to stakeholders.

Design, build, and continuously optimize ETL/ELT workflows that power our data landscape — from ingestion to delivery — with reliability and scale in mind....

• 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

• Develop and Implement: Build and maintain platform solutions that improve the reliability, security, and scalability of our Database Platform infrastructure.
• Operational Excellence: Apply cloud infrastructure, networking, and CI/CD best practices to support our operational data storage solutions.

We are looking for an enthusiastic PhD student to join our Integrated Cancer Research Laboratory at the CECAD Research Center in Cologne. The position is part of a newly funded project that aims to build and design digital twins for patients with cancer. The project builds on one of the largest and...

• Data pipeline development
• Data integration
• Data warehousing
• Data modelling
• Data quality and governance
• Performance optimization
• Collaboration with data scientists and analysts
• Technology selection
• Security and compliance
• Monitoring and troubleshooting

• Build agent loops and orchestration: tool use, structured outputs, business-rule enforcement, graceful failure
• Build the integration layer (via MCP) that lets agents securely call backend systems and business APIs
• Render model output into live, streamed, accessible UI via generative-UI protocols

• Architect and build the high-performance backbone of our data platform
• Focus on distributed computing stability and building effective caching strategies for large-scale operations
• Design ETL pipelines and architect resilient caching for complex dependency resolutions

Drive Architectural Strategy & Scalability: Partner across Data Science, Platform Engineering, and Product teams to design the technical architecture, data pipelines, and orchestration systems required for high-traffic AI services. Ensure the ecosystem supports highly available, low-latency...

• Architect complex data flow solutions, enabling transparent, versioned, and fully auditable computations
• Design the data layer by developing metadata and data lineage models fused by semantic graphs and numerical data

Act as a key expert for SAP S/4HANA data migration projects, with particular focus on Material Master and Production Master (I.e., BOMs, Work Centers, Routings and Production Versions)....

• Design of complex and scalable data solutions on the AWS cloud platform
• Development and implementation of complex and scalable data solutions on the AWS cloud platform
• Design and optimization of data pipelines
• Writing clean, efficient and maintainable SQL and Python code

• Support pipeline management and forecasting improvements for different business divisions using available data sources.
• Develop and maintain analytical tools and digital platforms to improve efficiency and self-service capabilities across the organisation.

• Design and implement modern data architectures and lakehouse solutions
• Provide technical leadership throughout the project lifecycle
• Collaborate with business stakeholders
• Create effort estimations and provide technical expertise during the pre-sales phase
• Mentor 3-6 person project teams

• Design, develop, and optimize scalable data pipelines for processing large-scale structured and unstructured data
• Ensure reliability, performance, and scalability of data systems
• Build solutions to handle real-time streaming data from multiple sources

• Build Data Pipelines: Design, build, and maintain scalable data pipelines for ingesting, transforming, and serving financial and operational data.
• Work with ERP Data: Integrate and model data from ERP systems and finance tools, including accounting, controlling, procurement, revenue, and cost data.

• Keep data moving: Build, run, and refine data pipelines and workflows (Python, Airflow/Cloud Composer) so they're reliable, fast, and easy to change
• Shape our data models: Use BigQueryand Cloud Spanner to design wellstructured, highperformance datasets for analytics and machinelearning use cases

• Implementation and maintenance of large-scale data pipelines and the Azure/Databricks data platform
• Building robust, scalable pipelines using Azure Databricks (PySpark / SQL)
• Integration of data ingestion, processing, transformation, and storage

• Build and run evaluation pipelines for LLM-based systems
• Analyze metrics, identify edge cases, and track quality
• Create and maintain Golden and Silver datasets
• Work with evaluation frameworks and tools (like Langfuse)
• Develop Python scripts for AI workflows (APIs, data processing, monitoring)