Python programmer állások, munkák adatbázisszakértő kategóriában

• Managing and migrating ETL pipelines between various source systems
• Validating pipeline build success and output data quality
• Communicating with business stakeholders and SME's regarding their respective data domain
• Analysing and resolving blockers and issues with ETL pipelines and data discrepancies

• 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

• As a Working Student AI Research Engineer for SLM Optimization (m/f/d/x), you will support the team in developing, refining, and managing caching mechanisms for Small Language Models (SLMs).
• You will contribute to the training and further development of models for cache prediction.

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....

• Development and operation of data pipelines
• Building data layers in OneDataLake (ODL) Central Data Store Consumer (CDSC)
• Balancing business and IT demands to build modern and efficient pipelines in public cloud environments
• Integration of data preparations into managed processes

You architect cloud and hardware solutions to scale AI workloads across GPUs and accelerators, while optimizing storage and networking for throughput, resilience, and cost efficiency....

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

• Define and further develop the Snowflake platform roadmap in alignment with enterprise data strategy and business priorities
• Establish the platform vision and manage priorities, demand intake and business requirements to maximize business value and support strategic objectives

• 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

• 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.

• Developing multi-scale and multi-modal representation learning methods for scientific imaging data (e. g., SEM, TEM, EBSD).
• Learning representations that are robust to scale changes, modality shifts, and domain differences across instruments and laboratories.

• Build and maintain dataset ingestion, cleaning, and versioning pipelines
• Design and operate labeling workflows including quality control and inter-annotator agreement tracking
• Own dataset testing including coverage analysis, class balance, leakage detection, dataset documentation

take responsibility as Tech Lead Search for the technical quality and architecture of our product retrieval and embedding capabilities based on OpenSearch....

• Analyze quality, usage, and diagnostic data from customer vehicles in the field
• Identify product issues, usage challenges, and opportunities to improve the customer experience
• Gain insights from various data sources, including vehicle diagnostics, customer complaints, and user behavior data