Data engineer állások Németországban (it programozás, fejlesztés)

Grow personally as a key player in the global finance team by developing the system landscape, creating data pipelines and BI products that facilitate automation and delivery of complex recurring and ad-hoc tasks across various functions, including global supply chain, sustainability, research...

Grow personally as a key player in the global finance team by developing the system landscape, creating data pipelines and BI products that facilitate automation and delivery of complex recurring and ad-hoc tasks across various functions, including global supply chain, sustainability, research...

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

• The data platform end to end: ingestion, storage, and the query paths that keep millions of records fast on screen. You design it, you build it, you run it in production.
• The platform layer, directly with the CTO: infrastructure, deployments, and the path to production for the whole team.

• Improve and extend the current analytics and AI infrastructure (built around Databricks)
• Drive the data platform by observing the fast Data and AI landscape and bringing in new ideas

• You design data pipelines for ingestion, curation, pseudonymization, and versioning.
• Furthermore, you implement reproducible training and finetuning builds for GenAI edge device models.
• You set up experiment tracking and artifact registries for model variants.

• 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.

Design, build, and maintain scalable data platforms and data & AI solutions tailored to business needs, including the development of governance structures and access control concepts...

Design and maintain scalable Lakehouse architectures and data pipelines using Azure Data Factory, Databricks, and Microsoft Fabric to support analytics and AI products....

• analyze complex databases, data streams, and large datasets to derive valuable insights and actionable recommendations
• develop, implement, and optimize algorithms and analytical models to improve existing business processes

• Development and optimization of AI applications for production and development processes
• Analysis of large production, quality, and process datasets
• Creation of dashboards and data models for data-driven decision-making
• Development of machine learning models for quality improvement

• Development and optimization of AI applications for production and development processes
• Analysis of large production, quality, and process datasets
• Creation of dashboards and data models for data-driven decision-making
• Development of machine learning models for quality improvement

End-to-end build-out of the COO data warehouse – from data modeling and pipeline development to the integration of relevant source systems and the delivery of usable data products...

Build and refine the forecasting models that directly shape our trading strategies and maximize the value of renewable energy in the market....

• Manage the IT Product Lifecycle for new and existing custom applications
• Take ownership of all activities related to the upcoming Mauser Customer B2B Portal
• Define and standardize the technology stack for custom application development

• You select and adapt base models for voice assistant and intelligence tasks.
• Furthermore, you produce clean, reproducible training, finetuning and evaluation pipelines to refine models for the problem at hand.

• Development and application of advanced data science methods, including transformer-based models, to marine and Arctic biodiversity data
• Work with large-scale biological and environmental datasets (sequencing data, eDNA)

• Collaborate with business stakeholders and leadership teams to gather requirements, develop, and support data modelling and BI solutions for organizational stakeholders
• Integrate different data sources into a cohesive data fabric, ensuring data consistency, accuracy and reliability

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...

• Lead and manage international research programs across AI, Data Science, Simulation, Processes, and Quantum Computing.
• Build and run multi-partner research consortia with world-leading universities, tech networks, and public funding agencies.