Cloud Engineer - GCP & Databricks
Tasks
- Advise clients on Databricks adoption and migrations
- Build Databricks Lakehouse solutions on GCP
- Build data pipelines batch and streaming
- Configure Databricks clusters and job scheduling
- Contribute to internal documentation and runbooks
- Create client deliverables including architecture diagrams specs and runbooks
- Define GCP landing zone standards
- Design Delta Lake tables with governance using Unity Catalog
- Design GCP architectures
- Develop PySpark and SQL workloads
- Ensure GDPR and data residency requirements
- Implement Databricks Workflows and Asset Bundles
- Implement data quality checks
- Implement infrastructure-as-code using Terraform
- Lead technical workshops and requirements gathering
- Manage deployments with CI/CD pipelines
- Present solution designs to stakeholders
- Support RFP and RFI solution design and estimates
- Support metadata management and data catalog initiatives
Perks/Benefits
- Access to training and industry experts
- Career advancement
- Hybrid work options
- International mobility
- Learning and development
- Professional development programs
- Remote work options
Skills/Tech-stack
Apache Airflow | Artifact Registry | Asset bundles | BigQuery | CI/CD | Cloud Build | Cloud Composer | Cloud Run | Cloud Storage | Cloud platform | DBT | Databricks | Databricks (asset) | Databricks Asset Bundles | Databricks Workflows | Dataflow | Dataplex | Delta Constraints | Delta Lake | Docker | Git | Google Cloud | Google Cloud Platform | Great Expectations | IAM | Looker | Looker Studio | MLflow | MLflow Model Registry | Model Registry | Organization Policies | Private Service Connect | Pub/Sub | PySpark | Python | REST APIs | SQL | Service Connect | Shared VPC | Terraform | Unity Catalog | VPC | Vertex AI
Education
Roles
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