Data Engineer II
Tasks
- Automate and scale model training inference and evaluation pipelines
- Build and optimize labeling and retraining pipelines
- Design and build ETL pipelines for analytics and ML workflows
- Design and evolve data lakehouse with schema partitioning and performance optimization
- Document data architecture and data lineage
- Ensure data quality and data governance
- Implement MLOps practices for model versioning and monitoring
- Perform code reviews and improve engineering best practices
- Use infrastructure as code and containerization for reproducible environments
Perks/Benefits
- 401k matching
- Employee equity plan
- Fertility and adoption reimbursement
- Flexible time off
- Health insurance
- Paid Holidays
- Paid parental leave
- Remote work
- Work from home funds
Skills/Tech-stack
AWS | Airflow | CI/CD | CloudWatch | Containerization | DBT | Dagster | Data Modeling | Databricks | Distributed Systems | ECS | ETL | Infrastructure as Code | Lambda | MLOps | Machine Learning | Model Monitoring | Pandas | Prefect | PySpark | Python | S3 | SQL | Terraform | “as-code”
Education
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