Senior Data Engineer (Python, SQL, Snowflake, Devops, Azure/ AWS, Co-pilot, Kubernetes, Docker)
Tasks
- Architect Snowflake environments
- Build ELT ETL batch frameworks
- Build cloud data solutions
- Build infrastructure using Terraform and CloudFormation
- Design data warehouses and data marts
- Design scalable ETL pipelines
- Enforce DevSecOps practices
- Implement CI/CD pipelines
- Implement Snowflake Tasks Streams Pipes
- Implement automated data testing and schema validation
- Implement data modeling Kimball and Data Vault
- Implement incremental loads and CDC
- Lead design and code reviews
- Mentor junior engineers
- Monitor lineage and SLAs
- Optimize warehouse compute cost and query performance
Perks/Benefits
- Employee Assistance Program (EAP)
- Flexible working environment
- LinkedIn Learning
- Mentorship
- Volunteer time off
Skills/Tech-stack
AWS | Airflow | Automated Lineage | Azure | Azure Bicep | Azure Data | Azure Data Factory | Azure DevOps | CDC | CI/CD | CloudFormation | Conftest | Containerization | DBT | Data Factory | Data Marts | Data Unit Testing | Data Vault | Data Warehousing | Data profiling | Delta Lake | DevSecOps | Dimensional Modeling | Docker | Event Driven | Event-driven architecture | GCP | GitHub Actions | GitLab CI | Great Expectations | Hudi | IAM | Iceberg | Incremental loading | Infrastructure as Code | Kafka | Kafka Streams | Kimball | Kinesis | Kubernetes | Marquez | Near-Real-Time data | Near-real-time | OPA | OpenLineage | Prefect | Pub/Sub | Pytest | Python | RBAC | Real Time | Real-time Data | SCD | SLA monitoring | SQL | Schema Validation | Schema evolution | Secret Scanning | Semantic layer | Snowflake | Star Schema | Step Functions | Streaming | Terraform | Unit Testing | Vulnerability scanning | Zero Trust | “as-code”
Education
N/A
Roles
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