Data Engineer
Tasks
- Automate experimental models for production use
- Collaborate with data scientists on modelling data preparation
- Deploy and scale machine learning models in production
- Design develop and manage ETL data pipelines
- Develop scripts for ETL automation
- Implement and maintain data quality checks
- Maintain and update curated feature store
- Monitor model performance and evaluation metrics
Perks/Benefits
- Career growth opportunities
- Continuing education programs
- Mental health benefits
- Performance incentives
- Product Discounts
- Retirement programs
- Well-being benefits
Skills/Tech-stack
Access Control | Active Directory | Apache Spark | Azure Active Directory | Azure Data | Azure Data Factory | Azure Data Lake | Azure Data Lake Storage | Azure Databricks | Azure Security | Azure Synapse | Azure Synapse Analytics | CI/CD | Data Factory | Data Ingestion | Data Lake Storage | Data Quality | Data scoring | Docker | Feature Store | GitLab | Jenkins | Kubernetes | MLflow | Machine Learning | Machine learning model deployment | Managed Identity | Model Deployment | Model Monitoring | PySpark | Python | R | RBAC | Role-Based Access | Role-Based Access Control | Synapse Analytics | TensorFlow Serving
Roles
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