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SeniorFull-timePythonAWSGCPAzureTerraformData ScienceCI/CDGitML
Salary Range
$26,520 - $35,880 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are seeking a highly skilled Senior Data Engineer to architect, build, secure, and optimize end-to-end data pipelines and enterprise-grade data platforms. The ideal candidate brings deep expertise in Python, Snowflake, modern cloud ecosystems, data warehousing design, and DevSecOps-led automation.
Key Responsibilities
- →Design, develop, and optimize scalable ELT/ETL pipelines using Python and SQL.
- →Build real-time, near-real-time, and batch frameworks using cloud-native services.
- →Implement incremental loads, CDC, SCD, schema evolution, and orchestration best practices.
- →Architect and manage Snowflake environments: warehouses, databases, schemas, resource monitors, RBAC, zero-copy clones.
- →Implement Snowflake Tasks, Streams, Pipes (Snowpipe) for event-driven data workflows.
- →Optimize compute cost and query performance using clustering, micro-partitioning, caching, and warehouse sizing.
- →Build and maintain solutions using cloud-native compute/storage components.
- →Design enterprise-grade Data Warehouses, Data Marts, and Semantic Layers.
- →Implement Kimball, Data Vault, and modern ELT-first design patterns.
- →Implement CI/CD pipelines for data engineering code (GitHub Actions / Azure DevOps / GitLab CI).
- →Enforce DevSecOps practices: secret scanning, IaC security gates, dependency scanning, policy-as-code (OPA/Conftest).
- →Build infrastructure using Terraform / Azure Bicep / CloudFormation.
- →Implement data unit testing, schema validation, and contract enforcement.
- →Lead design reviews, code reviews, and data platform roadmap discussions.
- →Mentor junior engineers and enforce engineering excellence.
Requirements
- ✓Deep expertise in Python and SQL for data engineering.
- ✓Experience with Snowflake and modern cloud ecosystems (AWS, Azure, GCP).
- ✓Strong understanding of data warehousing design and implementation.
- ✓Proficiency in DevSecOps practices and tools.
- ✓Experience with CI/CD pipelines and infrastructure as code.
- ✓Knowledge of data quality tools and techniques.
