Service
DevOps for Data Platforms
Data platforms deserve the same engineering discipline as application software: tests, pipelines, and rollback plans.
What It Is
Version-controlled, tested, and automated deployment for data infrastructure. Data platforms deserve the same engineering discipline as application software: tests, pipelines, and rollback plans.
Key Capabilities
- CI/CD pipelines for data pipelines and dbt projects
- Environment parity (dev/staging/prod) for data platforms
- Automated testing for data transformations
- Blue-green and canary deployments for pipeline changes
- Secrets and configuration management
- Observability and alerting for data infrastructure
The SEF Framework Applied to DevOps for Data Platforms
Every devops for data platforms engagement runs through Discover (assess current state), Design (target architecture), Engineer (build and test), Activate (deploy and monitor), and Scale (expand as needs grow) — see the full Sadbhagy Engineering Framework.