Enterprise Data & Generative AI Engineer
Tasks
- Automate documentation and testing
- Build data ingestion pipelines
- Build document processing chunking and embedding pipelines
- Collaborate on model training evaluation and monitoring
- Deploy and manage pipelines with infrastructure as code
- Develop ELT/ETL workflows
- Ensure data security, privacy, and regulatory compliance
- Implement data quality rules lineage tracking and metadata management
- Implement real time or near real time data flows
- Implement retrieval-augmented generation pipelines
- Integrate SAP and non SAP data in lakehouse platforms
- Maintain vector databases or embedding stores
- Model and harmonize SAP data structures
- Monitor data drift and AI data quality indicators
- Optimize pipeline performance and cost
- Prepare curated datasets for machine learning and generative AI
- Provide technical guidance on data architecture decisions
- Support synthetic data generation
Perks/Benefits
- 401k matching
- Employee resource groups
- Profit sharing plan
- RRSP matching
- RRSP or 401k matching
- Tuition reimbursement
- Tuition reimbursement program
Skills/Tech-stack
AWS | Airflow | Amazon SageMaker | Azure | CDS Views | DBT | Data Intelligence | Databricks | Databricks ML | Delta Lake | Embeddings | Faiss | GCP | IoT | Kafka | Kinesis | LLM | MLflow | Pinecone | Python | Retrieval-Augmented Generation | SAP BTP | SAP Data Intelligence | SAP Datasphere | SAP ODP | SAP S4HANA | SAP data | SQL | Snowflake | Snowpark | Spark | Streams & Tasks | Vector Databases | Vertex AI | Weaviate
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