AI Data Engineer
Tasks
- Apply data governance and security controls
- Build data architectures for agent workflows
- Build pipelines for near real time interactions and feedback signals
- Build scalable data pipelines
- Design data models for analytics and ML
- Develop ETL/ELT processes
- Implement automated data validation and schema checks
- Implement data quality controls for ML LLM pipelines
- Implement vector embedding storage and retrieval pipelines
- Improve reliability with testing observability documentation automation
- Monitor troubleshoot and resolve pipeline failures
- Translate data requirements into ingestion transformation serving
- Tune pipeline performance to reduce latency
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Azure | CI/CD | Data Validation | Data Warehousing | Data orchestration | Docker | ELT | ETL | GCP | Infrastructure as Code | Java | Knowledge graphs | Kubernetes | Lakehouse | NoSQL | Observability | Python | Retrieval | SQL | Scala | Schema management | Testing | Vector Databases | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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