Data Engineer III
Tasks
- Build automated data pipelines
- Build data catalogs for data discovery
- Build scalable ML inference systems
- Collaborate with analysts and data scientists to optimize data architecture
- Connect Databricks with enterprise data warehouses streaming platforms and business applications
- Create ETL ELT workflows for batch and streaming
- Create automated testing frameworks for analytical and ML workloads
- Create data models for machine learning and business intelligence
- Create monitoring and alerting for model performance data drift system health
- Design scalable data and machine learning infrastructure
- Design self service ML capabilities for model deployment and monitoring
- Develop data quality monitoring and validation systems
- Establish data lineage tracking quality monitoring and compliance controls
- Implement MLOps workflows with model training validation deployment monitoring
- Implement data governance standards and metadata management
- Implement medallion architecture
- Implement security and compliance controls
- Integrate ML systems with Tableau PowerBI Qlik Sense
- Integrate with Palantir Foundry systems
Perks/Benefits
- N/A
Skills/Tech-stack
Apache Spark | Automated testing | Batch Processing | Data Catalog | Data Drift | Data Governance | Data Lineage | Data Quality | Data drift monitoring | Databricks | Drift monitoring | ELT | ETL | MLOps | MLflow | Machine Learning | Machine Learning Inference | Medallion Architecture | Metadata Management | Model Deployment | Model Monitoring | Model Validation | Palantir Foundry | PowerBI | PySpark | Python | Qlik Sense | Spark SQL | Streaming Data | Tableau
Education
N/A
Roles
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