Data Engineer
Tasks
- Automate model training and deployment
- Build PySpark pipelines for feature engineering
- Build maintain structured datasets
- Collaborate with DevOps teams for containerization
- Design data architectures for analytics and modeling
- Design scalable ETL/ELT workflows
- Implement model versioning and artifact tracking
- Monitor data pipelines and troubleshoot failures
- Monitor data quality and drift detection
- Optimize Spark jobs for large scale data processing
- Support CI CD integration for ML pipelines
- Work with Data Scientists to productionize ML code
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Anomaly Detection | Apache Airflow | Apache Spark | Azure | DVC | Data Anomaly Detection | Data Architecture | Data Modeling | Data Monitoring | Data Pipeline Development | Data pipeline | Docker | Feature Store | GCP | Kubernetes | ML Lifecycle | MLflow | Pipeline Development | PySpark | PyTorch | SQL | Scikit-learn | TensorFlow
Education
Roles
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