EY - GDS Consulting - AI And DATA -AWS Data Engineer - Manager
INR 2000K-2700K (estimate) Mid-level Full Time
Tasks
- Build lakehouse data layers
- Build orchestration templates
- Create platform accelerators
- Design build production data pipelines
- Develop ingestion frameworks
- Enable agentic operations for data quality and incidents
- Implement Git based CI CD
- Implement data security controls
- Integrate AWS SageMaker for MLOps workflows
- Integrate data governance tools
- Integrate enterprise APIs and event services
- Manage data platform deployment monitoring logging
- Optimize Spark Glue EMR workloads
- Own Data SRE observability and reliability
- Support SageMaker pipelines feature store model registry model monitor
Perks/Benefits
- Career growth opportunities
- Flexible work approach
- Learning and development
- Support coaching feedback
Skills/Tech-stack
API | AWS Bedrock | AWS CloudTrail | AWS Glue | AWS Glue Data Catalog | AWS KMS | AWS Lambda | AWS MWAA | AWS Secrets | AWS Secrets Manager | AWS Step Functions | Amazon Athena | Amazon CloudWatch | Amazon EMR | Amazon EventBridge | Amazon IAM | Amazon Macie | Amazon Redshift | Amazon S3 | Amazon SageMaker | Amazon Web Services | Apache Airflow | Azure DevOps | CloudFormation | Collibra | Data Catalog | Docker | EKS | Feature Store | FinOps | Git | GitHub Actions | Glue Data Catalog | Immuta | Infrastructure as Code | Integration Testing | Jenkins | Kubernetes | Lake Formation | Microsoft Purview | Model Monitor | Model Registry | OpenTofu | Policy-as-Code | PySpark | Python | SQL | SRE | Sagemaker Pipelines | Secrets Manager | Shell Scripting | Step Functions | Terraform | Unit Testing | Web Services | “as-code”
Education
N/A
Roles
AI | AI Data Platform Engineer | Data Engineer | Data Platform | Data Platform Engineer | Engineer | Platform | Platform Engineer
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