Senior AI Data Engineer
Tasks
- Build data pipelines for training and inference
- Create feature stores metadata services data APIs
- Deliver data pipelines for MLOps and AgenticOps
- Design data platforms for AI
- Design fault tolerant event driven data pipelines
- Develop LLM RAG embeddings architecture
- Implement automated data validation profiling lineage observability monitoring
- Implement data governance security privacy compliance controls
- Optimize distributed data processing performance scalability reliability cost
- Prepare production datasets for model deployment
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Amazon Kinesis | Apache Airflow | Apache Spark | Automated testing | Azure | Azure Data | Azure Data Factory | Azure Event | Azure Event Hubs | CI/CD | Cloud platform | Data Factory | Data Governance | Data Lakes | Data Lineage | Data Modeling | Data Processing | Data Warehouses | Distributed data | Distributed data processing | Embeddings | Event Hubs | Feature Engineering | Google Cloud | Google Cloud Platform | Infrastructure as Code | Kafka | Lakehouse | Metadata Management | Monitoring | Object storage | Observability | Python | RAG | Retrieval-Augmented Generation | SQL | Semantic Search | Vector Databases | Version control | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Data Engineer | Data Engineer | Engineer | Senior AI Data Engineer
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