Senior Consultant AI Data Engineering - Microsoft Azure (all genders)
Tasks
- Build LLM-based applications
- Build conversational BI solutions
- Build data pipelines
- Create end to end data architectures
- Create semantic data models
- Design and implement data platforms
- Develop agentic components for pipeline automation
- Develop data products for analytics
- Develop lakehouse architectures
- Handle data integration transformation governance
- Implement RAG architectures
- Implement data quality monitoring
- Integrate cloud data platforms
- Integrate data engineering with AI engineering
- Plan platform modernization and migration paths
- Provide AI in data strategy consulting
- Support customer tool selection and target architecture
Perks/Benefits
- Career Growth Model
- Coaching
- Corporate Benefit Program
- Electrified Vehicle
- Employee share ownership plan
- Flexible career model
- Generous paid time off
- Mobile work
- Sabbatical options
- Training budget
- Travel support
Skills/Tech-stack
AI Foundry | APIs | Agentic AI | Azure AI | Azure AI Foundry | Azure Data | Azure Data Factory | Azure Synapse | CI/CD | Cloud Data | Cloud Data Warehouse | DBT | Data Factory | Data Quality | Data Warehouse | Data models | Databricks | ELT | ETL | Infrastructure as Code | LLM | Lakehouse | MLOps | Microsoft Azure | Microsoft Fabric | Power BI | Power Platform | PySpark | Python | RAG | SQL | Semantic data | Semantic data models | Snowflake | “as-code”
Education
N/A
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