Data analyst állások, munkák programozó, fejlesztő kategóriában

• Ownership of data engineering features, architecture, and code quality
• Design, implementation, and maintenance of Databricks-based data pipelines and workflows
• Building and optimization of ETL/ELT processes using Apache Spark on Databricks

• Delivery on complex data engineering projects across industries
• Leading small delivery teams
• Managing customer relationships alone or with a Project Manager
• Mentoring more junior engineers
• Evaluating the quality of junior engineers' work
• Contributing to hiring best-in-class data engineers

• Design, implement, and manage Azure cloud infrastructure to support Databricks and data platform workloads
• Build and maintain Azure resources including Resource Groups, VNets, Key Vaults, Storage Accounts, and Azure Active Directory (AAD) integrations

Design, develop, test, document, and deploy high quality Salesforce solutions leveraging the latest capabilities of the Einstein 1 Platform, Lightning Web Components, and modern Apex patterns...

Design of high quality Salesforce solutions leveraging the latest capabilities of the Einstein 1 Platform, Lightning Web Components, and modern Apex patterns...

About Givaudan Givaudan is a global leader in Fragrance & Beauty and Taste & Wellbeing. We celebrate the beauty of human experience by creating for happier, healthier lives with love for nature. Together with our customers we deliver food experiences, craft inspired fragrances and develop beauty...

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...

• Shaping transformations in S/4HANA transformation projects from planning to execution
• Designing and developing SAP-based software solutions, architectures, and transformation scenarios
• Executing SAP data migrations and guiding colleagues throughout the process

Junior AI Data Engineer (graph modeling) Degree: Done. Next stop: Building the data infrastructure that powers the digital world. Everyone hypes up the front-end, but we know the truth-it's the data pipelines that do the heavy lifting. If you're a fresh Data Engineer hungry for massive scale, it's...

• 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

• Development, maintenance, and support of cloud-based data operation infrastructure and production data pipelines
• Design, implementation, operation, and optimization of Azure data services and Databricks workloads

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

• 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.

• Technical leadership post-sales for strategic customers in big data project design and implementation
• Identification and driving of new initiatives to turn data into actionable business value aligned with business goals

• 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

• Delivery on complex projects individually or by leading small delivery teams
• Management of customer relationships alone or in collaboration with a Project Manager
• Support of pre-sales process
• Mentoring of more junior engineers
• Contribution to hiring best-in-class data talent

• 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.

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...