Senior AI Data Engineer
Tasks
- Apply data security measures
- Build knowledge graphs storage systems
- Build resilient data architectures
- Build scalable data models
- Create vector embeddings storage and retrieval systems
- Design scalable data pipelines
- Develop event-driven pipelines
- Develop feature ready datasets
- Ensure data pipeline reliability
- Establish data observability
- Implement ETL processes
- Implement data governance
- Implement data validation
- Implement lineage tracking
- Implement streaming data pipelines
- Maintain semantic layers
- Monitor and troubleshoot pipelines
- Optimize data platform scalability
- Optimize storage for AI datasets
- Optimize system latency for agent decision making
- Partition and index large scale datasets
- Perform quality checks for training datasets
- Reduce data processing costs
- Run schema testing
- Set up monitoring frameworks
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Airflow | Azure | Benchmarking | CI/CD | Dask | Data Lakehouse | Docker | Feature Store | Flink | GCP | Kafka | Knowledge graphs | Kubernetes | LLM Evaluation | Milvus | NoSQL | Pinecone | Prompt engineering | PyTorch | Python | RAG | RLHF | Ray | Retrieval-Augmented Generation | SQL | Scala | Semantic Caching | Spark | Streaming Data | TensorFlow | Terraform | Vector Database | Vector embeddings | Weaviate
Roles
AI | AI Data Engineer | Data Engineer | Engineer | Senior Data Engineer
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