Senior Data Platform Engineer
Tasks
- Apply Unity Catalog governance
- Build ML pipelines for feature engineering and training
- Build and maintain Databricks platform infrastructure
- Conduct code reviews and technical design
- Deploy and serve machine learning models
- Design data and ML pipelines
- Enforce data modeling standards and medallion architecture
- Evaluate integrate and govern new data sources
- Implement Delta Lake table architecture
- Implement data quality and monitoring frameworks
- Mentor engineers and document runbooks
- Operationalize models from experimentation to production
- Optimize pipeline performance cost and reliability
- Orchestrate workflows with Databricks Workflows
- Track experiments with MLflow
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Agile | Azure | CI/CD | DBT | Data Modeling | Data Quality | Databricks | Databricks Workflows | Delta Lake | Dimensional Modeling | Experiment tracking | Feature Engineering | Feature Store | GCP | Git | Infrastructure as Code | Kafka | Kinesis | MLflow | Machine Learning | Model Deployment | Model Training | Monitoring | Observability | PySpark | Python | SQL | Scrum | Spark | Spark Structured Streaming | Structured Streaming | Terraform | Unity Catalog | “as-code”
Education
N/A
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