Data Engineer (PySpark & AWS)
Tasks
- Automate infrastructure provisioning using Terraform or CDKTF
- Build CI CD pipelines and containerized solutions
- Build ETL pipelines using AWS Glue Lambda and Step Functions
- Collaborate with business intelligence teams for reporting and analytics
- Design manage data lakes on Amazon S3
- Develop distributed data processing workflows using PySpark
- Implement data governance using AWS Lake Formation
- Implement logging observability and monitoring
- Optimize data storage using Apache Iceberg and Parquet
- Participate in Agile/Scrum ceremonies and planning
- Perform root cause analysis and optimize performance
Perks/Benefits
- N/A
Skills/Tech-stack
API Gateway | AWS API | AWS API Gateway | AWS Athena | AWS CDK | AWS Glue | AWS Lake Formation | AWS Lambda | AWS Step Functions | Access Control | Agile Scrum | Amazon S3 | Apache Iceberg | CDKTF | CI/CD | Data Governance | Data Pipelines | Data Security | Docker | DynamoDB | ETL | Infrastructure as Code | Lake Formation | Logging | Monitoring | Observability | Parquet | PySpark | Python | Schema evolution | Step Functions | Terraform | “as-code”
Education
N/A
Roles
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