Data Engineering Professional II
INR 1500K-2600K (estimate) Mid-level Full Time
Tasks
- Author and maintain validation deliverables and technical documentation
- Build ML systems for GxP compliance
- Build and manage ML infrastructure on AWS
- Contribute reusable templates and self service tooling
- Design build and operate end to end ML pipelines
- Establish observability and incident response practices
- Handle PHI PII with de identification and role based access
- Implement CI CD for ML and data assets
- Implement audit trails electronic records and access controls
- Implement model and data monitoring drift detection and alerting
- Integrate Databricks with AWS securely
- Maintain feature stores and data contracts
- Productionize machine learning models for regulated services
- Stand up and maintain model registries and model versioning
Perks/Benefits
- N/A
Skills/Tech-stack
21 CFR | 21 CFR Part 11 | ALCOA+ | AWS | AWS CDK | AWS CloudFormation | AWS Lambda | AWS Step Functions | Amazon Bedrock | Amazon ECR | Amazon ECS | Amazon EKS | Amazon Kinesis | Amazon S3 | Amazon SageMaker | Apache Spark | CFR Part 11 | CI/CD | CloudWatch | Computer system | Computer system validation | Data Monitoring | Data Quality | Databricks | Databricks Jobs | Delta Lake | Docker | Drift Detection | Feature Store | GAMP 5 | GDPR | GitHub Actions | GitLab CI | GxP | HIPAA | IAM | Infrastructure as Code | Jenkins | Kafka | Kubernetes | MLflow | Model Monitoring | Model Registry | Part 11 | PySpark | Python | RAG | SQL | Step Functions | System validation | Terraform | Unity Catalog | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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