IT Principal Data Engineering
Tasks
- Align platform capabilities with AI ML goals
- Build end-to-end data science pipelines
- Conduct code reviews
- Design ETL pipelines
- Design data science platform architecture
- Develop outbound data feeds
- Ensure auditable reproducible outputs
- Ensure data quality and lineage
- Implement MLOps practices
- Implement data governance privacy and security
- Implement engineering templates
- Manage model versioning
- Mentor data engineers
- Monitor deployed models
- Optimize ETL pipelines
- Perform feature engineering
- Serve model inference
- Train machine learning models
- Translate technical concepts for stakeholders
Perks/Benefits
- 401k match
- Career development opportunities
- Dental insurance
- Employee assistance program
- Employee referral program
- FSA
- HSA
- Medical insurance
- Paid time off
- Tuition reimbursement
- Vision insurance
- Wellbeing program
Skills/Tech-stack
APIs | AWS | Azure | Azure Synapse | Batch inference | BigQuery | Data Modeling | Data Vault | Databricks | Distributed Systems | ELT | ETL | FTP | Feature Engineering | Feature Stores | GCP | Kimball | MLflow | MPP databases | Machine Learning | Machine learning model deployment | Model Deployment | Model Monitoring | PyTorch | Python | Real Time | Real-time Inference | SQL | Scikit-learn | Snowflake | Spark | TensorFlow | Teradata | XGBoost
Education
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