Sr. Engineer, Data - Archimedes
Tasks
- Build AI ready data products for machine learning and generative AI
- Build bronze/silver/gold data layers
- Build secure data engineering controls encryption RBAC and masking
- Conduct architecture reviews and provide technical mentorship
- Design ETL pipelines for structured and unstructured data
- Design Lakehouse architecture
- Develop canonical data models
- Develop data governance and metadata frameworks
- Develop data integration pipelines using cloud services
- Implement CI CD workflows for data pipeline deployment
- Implement DataOps practices including testing monitoring and quality validation
- Implement feature engineering vectorization and semantic search pipelines
- Monitor and troubleshoot data pipeline performance
- Serve as enterprise data engineering technical lead
- Support healthcare data integration patterns
Perks/Benefits
- N/A
Skills/Tech-stack
API | AWS Glue | AWS Lambda | Automated testing | Azure Data | Azure Data Factory | Azure Data Lake | Azure Data Lake Storage | Azure Data Lake Storage Gen2 | Azure Databricks | Azure DevOps | Azure Functions | CI/CD | Data Factory | Data Lake Storage Gen2 | Data Lineage | Data Management | Data Modeling | Data Quality | Data masking | DataOps | Delta Lake | ETL | Encryption | Event Grid | Event Hub | Feature Engineering | Generative AI | GitHub Actions | HIPAA | Jenkins | Machine Learning | Master Data | Master Data Management | Metadata Management | Observability | PostgreSQL | RBAC | Retrieval-Augmented Generation | Row Level Security | SOC 2 | SQL | SQL Server | Semantic Search | Service Bus | Unity Catalog | Vectorization
Education
N/A
Roles
Architect | Data Architect | Data Engineer | Engineer | Senior Data Engineer
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