Sr. Data Engineer
Tasks
- Build and operate data ingestion and transformation pipelines
- Build machine learning pipelines for training and deployment
- Define infrastructure as code and manage CI CD pipelines
- Design scalable data platforms
- Develop ML feature stores and reusable feature pipelines
- Develop and maintain data models and feature datasets
- Develop data lake lakehouse and warehouse architectures
- Develop unit integration and data quality tests
- Document data pipelines ML pipelines and infrastructure
- Implement data pipelines for unstructured data embeddings and vector stores
- Implement data privacy security and access control best practices
- Integrate LLM based agents and agentic workflows
- Optimize performance scalability resilience and efficiency
- Perform peer code reviews and maintain coding standards
- Support ML model lifecycle management and lineage
Perks/Benefits
- 401k match
- Disability insurance
- Employee assistance program
- Generous paid time off
- Health insurance
- Life insurance
- Parental leave
- Volunteer time off
Skills/Tech-stack
AWS | CI/CD | DBT | Data Engineering | Data Governance | Data Lake | Data Mart | Data Modeling | Data Warehouse | Databricks | Embeddings | Feature Stores | Git | Infrastructure as Code | LLM Agents | Lakehouse | MLOps | Machine Learning | Machine Learning Pipelines | Model Monitoring | Prompt engineering | PySpark | Python | Retrieval-Augmented Generation | SQL | Vector Databases | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
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