Vice President, Data Engineering
San Francisco, California (Suite 400), United States
USD 254K-407K Executive-level Full Time
Tasks
- Architect scalable batch and streaming data pipelines
- Define architecture standards and engineering best practices
- Define end to end cloud native data platform architecture
- Design and implement core data platform components
- Design and implement data governance frameworks
- Drive DevOps transformation for data platforms
- Establish enterprise cloud security standards
- Implement lakehouse architecture with medallion model
- Improve performance scalability reliability and cost efficiency
- Lead data engineering and platform engineering technical leadership
- Mentor engineers and build high-performing teams
Perks/Benefits
- N/A
Skills/Tech-stack
ARM Templates | AWS | AWS CloudFormation | AWS Glue | AWS Lake Formation | AWS Lambda | Access Control | Agile | Amazon CloudWatch | Amazon EC2 | Amazon ECS | Amazon S3 | Apache Flink | Apache Spark | Azure | Azure Data | Azure Data Factory | Azure DevOps | Azure Fabric | Azure Kubernetes | Azure Kubernetes Service | Azure Monitor | Azure Purview | Azure Synapse | Azure Synapse Analytics | CI/CD | Cloud Cost Optimization | Cost Optimization | Data Catalog | Data Classification | Data Factory | Data Lineage | Databricks | Docker | ELK | ELT | ETL | Encryption | GDPR | GitLab CI | GitLab CI/CD | HIPAA | IAM | Infrastructure as Code | Kubernetes | Kubernetes Service | Lake Formation | Lakehouse | MLOps | Machine Learning | Machine Learning Pipelines | Monitoring | Network Security | Observability | PySpark | Scrum | Synapse Analytics | Terraform | “as-code”
Education
N/A
Regions
Countries
States
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