AI Data Engineer
Tasks
- Build near real time pipelines and feedback signals
- Build vector embedding stores pipelines and retrieval
- Design data architectures for agent workflows
- Design data models
- Design data pipelines
- Develop ETL/ELT processes
- Implement automated data validation and schema checks
- Implement data governance and security controls
- Improve reliability with testing observability and automation
- Maintain scalable data infrastructure
- Monitor troubleshoot data pipeline failures
- Translate data requirements into ingestion and transformation
- Tune performance to reduce latency
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Automation | Azure | CI/CD | Data Governance | Data Modeling | Data Security | Data Validation | Data Warehousing | Docker | ELT | ETL | GCP | Infrastructure as Code | Java | Knowledge graphs | Kubernetes | Lakehouse | NoSQL | Observability | Orchestration | Python | Retrieval | SQL | Scala | Schema Testing | Streaming | Testing | Vector Databases | Vector embeddings | “as-code”
Education
Roles
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