GCP Platform Engineer

Role:

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Experience:

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Role & responsibilities

Platform Build & Engineering:

• • Architect, deploy, and configure GCP data platform components (Dataproc clusters, Composer environments, Dataflow workers, GCS storage controls, IAM policies).
• • Build Terraform-driven reusable templates and configuration blueprints for platform provisioning.
• • Implement security & governance controls CMEK, VPC Service Controls, org policies, workload identity, IAM least privilege.
• • Define platform standards autoscaling rules, cluster profiles, dependency packaging, environment provisioning workflows.

L3 Troubleshooting & Developer Enablement:

• • Serve as platform L3 escalation for engineering teams to debug Dataproc/YARN execution failures, Dataflow backlog or performance bottlenecks, Composer scheduler or DAG dependency errors.
• • Provide reference architectures, runbooks, onboarding documentation.
• • Enable self-service platform usage via templates, automation and tooling.

Automation, CI/CD & Tooling:

• • Build internal automation to provision environments using IaC and scripting.
• • Integrate CI/CD pipelines (Cloud Build, GitHub Actions) for Composer DAGs, Dataflow templates and platform configurations.
• • Develop frameworks for dependency packaging, deployment workflows and observability.

Performance, Reliability & Platform Evolution:

• Monitor platform health using Cloud Monitoring, tune performance, and scale capacity.
• Optimize cost across clusters/jobs, introduce budget controls and quotas.
• Participate in platform roadmap, architecture modernization and platform upgrades.

Preferred candidate profile

Core GCP Data Services Expertise:

• Dataproc – cluster config, init-actions, HA setups, autoscaling, debugging YARN.
• GCS – IAM policy design, lifecycle management, CMEK, cross-project sharing.
• Dataflow – Flex Templates, worker sizing, backlog handling, tuning pipelines.
• Composer – Airflow deployments, dependency management, scaling, DAG troubleshooting.

Engineering Skills:

• Terraform (preferred) or IaC experience.
• Python or Shell scripting for automation.
• CI/CD integration for platform workloads.
• Spark/Hadoop understanding for job failure troubleshooting.

Leadership & Collaboration:

• Ability to lead platform roadmap execution while remaining hands-on.
• Strong collaboration and communication skills across architecture, security & engineering teams.
• Ownership mindset and documentation capability.

Preferred Certifications

• Google Professional Data Engineer
• Google Cloud Architect
• Google Associate Cloud Engineer