AI Data Engineer
Tasks
- Align data input and output requirements
- Build ELT pipelines
- Build ETL pipelines
- Design data ingestion pipelines
- Develop RAG pipelines
- Develop feature engineering pipelines
- Develop production services with REST APIs
- Ensure data governance and security standards
- Expose data and AI capabilities
- Implement CI/CD pipelines
- Implement data integration pipelines
- Implement data validation and testing
- Integrate AI services into data workflows
- Maintain data ingestion standards and reusable frameworks
- Optimize cost and throughput
- Set up data monitoring and observability
- Troubleshoot pipeline failures
Perks/Benefits
- N/A
Skills/Tech-stack
AWS CDK | Access Control | Azure | CI/CD | Content Understanding | Data Lineage | Data Monitoring | Data Quality | Data Validation | Distributed Processing | Document Understanding | ELT | ETL | Embeddings | Feature Engineering | GitHub Actions | LLM APIs | Logging | Metrics | Multimodal Data | Observability | Python | REST APIs | Retrieval-Augmented Generation | Role-Based Access | Role-Based Access Control | Search | Semi-structured | Semi-structured Data | Structured data | Terraform | Tracing | Unstructured Data
Education
N/A
Roles
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