M18 - Data Engineer
Tasks
- Build ETL processes
- Conduct peer code reviews
- Create data models and data marts
- Create technical documentation
- Deploy and integrate machine learning models with AWS SageMaker
- Design and develop RESTful APIs
- Design, develop, and maintain data pipelines
- Develop Python scripts for data processing in AWS Glue
- Develop data virtualization solutions
- Implement CI/CD pipelines
- Implement Data Governance and Master data management
- Implement data security and compliance
- Integrate internal and external data sources
- Maintain data warehouses data lakes and operational data stores
- Optimize database performance with indexing and query tuning
- Participate in agile ceremonies
- Perform data cleansing transformation and loading
- Write and optimize VQL and SQL queries
Perks/Benefits
- N/A
Skills/Tech-stack
AWS Glue | Amazon Athena | Amazon RDS | Amazon S3 | Amazon SageMaker | CI/CD | Data Governance | Data Lakes | Data Management | Data Modeling | Data Store | Data Warehousing | Database performance | Database performance tuning | Denodo | ETL | GitLab | Master Data | Master Data Management | Operational data | Operational data store | Performance Tuning | Power BI | Python | REST API | SQL | Tableau | VQL
Education
N/A
Roles
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