Data engineer állások Németországban (it programozás, fejlesztés)

• 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

• Take ownership of data engineering initiatives within projects and act as a technical lead towards customers
• Design, build and evolve scalable data platforms and architectures aligned with business goals

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...

• 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

Scalable Data Pipelines: Design, build, and operate automated pipelines on Apache Airflow to transform largescale automotive datasets reliably and on schedule....

• Conceptualizing secure workflows for international submission of sensitive medical imaging data
• Defining architectural concepts for the benchmarking and evaluation platform, including controlled and secure execution of externally submitted models

Acting as Release Engineer / Technical Lead for one of Ambu's core AI/ML initiatives, providing technical direction and ensuring alignment across software, algorithms, systems, and regulatory requirements....

• Contribute to pioneering technical advances to the field of foundation models on structured data, as well as exploring world models for solving business problems.
• Define the data, training, and experimentation environment to enable scalable access to data and compute.

Own SEO data pipelines end-to-end. Design, build, and maintain automated pipelines that power all SEO analytics, from ingestion through transformation to dashboarding....

• 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

• 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

• As a Senior Data Scientist you will act as a mentor and trainer, helping to build and share knowledge across the organization.
• You will be responsible for developing and conducting expert training programs, including direct training sessions and project-based mentoring.

Strategy and Leadership: Define, communicate, and execute the overall Data Science roadmap and vision for the Generative AI function, ensuring alignment with N26's product and business goals....

• Translate business requirements into technical solutions through workshops, prototyping, and iterative delivery
• Collaborate with customers across the delivery lifecycle (workshops, reviews, UAT) to refine and optimize solutions

• Design, implement, and manage document embedding storage solutions
• Develop and optimize processes for efficient information extraction from documents, including handling complex nested structures, to create
• and populate databases for our advanced chatbot applications

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...

• 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.

Play a key role in shaping Group-wide data governance by ensuring data is trusted, discoverable, and responsibly used across the organization, with a strong focus on the Group Data Catalog (Data Galaxy)...

• Conduct independent research at the intersection of data science and public policy with a focus on ML/AI, causal inference, and/or computational methods;
• Collaborate with faculty and Data Science Lab members on joint research projects;

• 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.