Manager, Data Engineer, Data Innovation Office
Tasks
- Apply feature engineering and validate datasets for modeling
- Automate monitoring scaling and disaster recovery
- Build data pipelines optimized for performance and cost
- Cleanse transform and preprocess data for analytics and machine learning
- Collaborate with researchers data scientists and stakeholders
- Create CI/CD pipelines for data platforms
- Design and build scalable secure research data environments
- Design and implement Data Lakes and Data Warehouses
- Develop ETL pipelines for batch and real time processing
- Develop data models for reporting and dashboards
- Establish automated data quality monitoring and validation rules
- Guide data engineering teams to deliver project plans
- Implement infrastructure-as-code for deployments
- Integrate data platforms with existing infrastructure
- Manage data governance compliance and run audits
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Azure | Batch Processing | CI/CD | Cloud platform | Data Governance | Data Lakes | Data Modeling | Data Pipelines | Data Quality | Data Warehousing | Docker | ETL | Google Cloud | Google Cloud Platform | Infrastructure as Code | Kubernetes | Machine Learning | Pulumi | Real Time | Real-time Processing | Terraform | Time processing | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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