Data engineer állások Németországban (it programozás, fejlesztés)

• Build and own scalable data pipelines and integration solutions our data warehouse and data platform.
• Integrate and transform data from ERP, CRM, finance, and other enterprise systems.
• Ensure high standards of data quality, reliability, performance, and operational excellence.

Building efficient and scalable ETL/ELT processes to ingest, transform, and load data from various structured and unstructured sources (databases, APIs, streaming platforms) into BigQuery and Cloud Storage...

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 and develop backend data objects and data models that provide reliable, analytics-ready data for downstream BI dashboards and reporting solutions...

• 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.

Predictive ML: Build models for lead generation, demand forecasting, residual value forecasting, portfolio steering, and fraud detection....

• Become familiar with our technology stack and learn everything about the high-level job market and our job classification framework.
• Research and select the most high-level jobs and classify them according to our key criteria.

Advise business units and senior stakeholders on AI opportunities, strategic priorities, target operating models, and the practical implications of emerging AI technologies...

Work in our Data & AI Center of Excellence (DACE) in close collaboration with a diverse team of 45 data scientists and AI engineers from various disciplines...

• Own the end-to-end forecasting and price-elasticity models at the core of our pricing engine — from feature and model research through evaluation, deployment, and continuous monitoring
• Scale the forecasting architecture to meet growing demand for granular, product-level forecasts

Own and continuously refine the product vision, roadmap, and backlog for the AI-driven reservoir simulator, aligned with business goals and market demands....

• Develop and integrate AI (Artificial Intelligence) components (LLM agents, RAG pipelines, API integrations) into existing platforms
• Develop software using TypeScript in modern technology stacks (NestJS, Vue 3), including testing and code reviews

Contribute to our Text Analytics and Generative AI projects - from data preparation and analysis through model and prompt evaluation to the development of new features....

• Take ownershipof the pricing tool used by the commercial department
• Develop and optimize end-to-end pricing strategies, including algorithm development, implementation, and continuous performance monitoring

• As a Bachelor's Thesis Student – User Feedback & Data Analytics (m/f/d/x), you will support the team in analyzing existing user research findings and evaluating user feedback.
• You will process and analyze existing quantitative user data to identify relevant insights.

• Development and implementation of interfaces between clinical data sources, medical knowledge bases, and local LLM/agent-based systems
• Development of high-performance data pipelines for loading, structuring, validating, and further processing interoperable health data

• Design and build AI agents and workflows that solve concrete business problems
• Take technical ownership of applied AI solutions - from architecture decisions to engineering standards and code quality
• Build enterprise-grade solutions on modern AI platforms, mainly Azure

• Formulate a focused research question in alignment with business and academic supervisors
• Conduct a structured analysis of relevant supply chain, planning, or transformation processes
• Develop and validate a practical, data-driven solution for the defined business challenge

• Take ownership of IT risk, business continuity and operational resilience activities.
• Assess complex IT, vendor, solution and process-related risks and provide clear, actionable recommendations.

• Each project starts with an open decision problem and incomplete ERP and Excel data. The customer needs to know early which result the available data supports.
• We run several customer projects in parallel, without a standard process for kickoff, scoping, data and first result.