Python programmer állások, munkák adatbázisszakértő kategóriában

• 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

• 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, and dataset documentation

Design, implement, and maintain data pipelines that integrate multimodal, structured and unstructured clinical and surgical data from proprietary data collection systems and electronic health record systems, supporting both retrospective analyses and secure live or near-real-time data flows in...

• 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.

The customer's decision problem. Sit with the people who plan today, understand capacities, costs, lead times and the constraints nobody wrote down, and turn it into a model whose answer a plant manager acts on. Inventory, scheduling, supply shortages, order prioritization: the decisions that...

• 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

• 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

Customer models, end to end. Turn a planning problem, with its capacities, costs, lead times and shift plans, into a model whose answer a plant manager acts on. That includes the data it runs on: ERP and Excel exports, and catching the numbers that cannot be right before the customer does....

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...

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...

• 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

• 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.

• Pioneer technical advances to the field of foundation models on structured data, as well as exploring world models for solving business problems.
• Gain new insights by bringing together rich semantic context with large scale business data.

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

You will join a highly quantitative, forward-thinking Commercial team at the heart of the energy transition. In this role, you combine advanced modelling, data analytics and market expertise to shape hedging strategies, develop innovative energy products and support strategic decision-making at...

• Lead develop AI services from PoC to Production
• Lead the development of a best practice framework for AI development (both narrow and GenAI) for all dev streams and teams
• Lead the definition, evolution and drive the setup of infrastructure architecture for the AI applications we are building

• Data assets and strategy: Own pre-training, evaluation and metadata assets, shape their strategy and expand them with new data sources.
• Data roadmap and prioritization: Maintain the short- and long-term roadmap, manage the extraction backlog and coordinate dependencies.

• Lead the architectural vision and strategic direction for AI and machine learning systems across a distributed team in India and Europe.
• Architect unified, scalable and secure AI systems that supports international data sovereignty and regional privacy regulations.

Design, train, and evaluate machine learning models for manufacturing use cases such as quality prediction, anomaly detection, predictive maintenance, and process optimisation, covering the full ML lifecycle from problem definition to performance tuning....

• 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)