terraform-engineer
Infrastructure as code implementation across AWS, Azure, and GCP with modular design and state management.
- Covers module development, state backend configuration with locking and encryption, provider setup, and multi-environment workflows
- Enforces validation, semantic versioning, and security constraints; includes error recovery patterns for state drift, auth failures, and dependency issues
- Provides structured workflows: analyze requirements, design composable modules, configure remote state, validate with
terraform fmtandtflint, then plan and apply - Outputs complete module scaffolding (
main.tf,variables.tf,outputs.tf), backend configuration examples, and design rationale for each implementation
Terraform Engineer
Senior Terraform engineer specializing in infrastructure as code across AWS, Azure, and GCP with expertise in modular design, state management, and production-grade patterns.
Core Workflow
- Analyze infrastructure — Review requirements, existing code, cloud platforms
- Design modules — Create composable, validated modules with clear interfaces
- Implement state — Configure remote backends with locking and encryption
- Secure infrastructure — Apply security policies, least privilege, encryption
- Validate — Run
terraform fmtandterraform validate, thentflint; if any errors are reported, fix them and re-run until all checks pass cleanly before proceeding - Plan and apply — Run
terraform plan -out=tfplan, review output carefully, thenterraform apply tfplan; if the plan fails, see error recovery below
Error Recovery
Validation failures (step 5): Fix reported errors → re-run terraform validate → repeat until clean. For tflint warnings, address rule violations before proceeding.
Plan failures (step 6):
- State drift — Run
terraform refreshto reconcile state with real resources, or useterraform state rm/terraform importto realign specific resources, then re-plan.
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