GCP Cloud Engineer

Role Overview

We are seeking a highly skilled and motivated GCP Cloud Systems Engineer to lead the design, deployment, and operational excellence of our Google Cloud Platform (GCP) environment. A key focus for this role will be to work with a transitional team of our legacy on-premises environment to a modern, cloud-native orchestration framework.

The ideal candidate is a hybrid of a Systems Administrator and a DevOps Engineer— someone who is comfortable writing Terraform code, troubleshooting networking issues or migrating a legacy scheduler to Airflow and providing support.

Key Responsibilities

Infrastructure & Automation

Design, build, and maintain scalable cloud infrastructure using Infrastructure as Code (IaC), primarily via Terraform.

Deploy and manage optimized Compute Engine’s, Google Kubernetes Engine (GKE) clusters, serverless options like Cloud Run or Cloud Functions.

Configure and maintain Virtual Private Clouds (VPCs), including subnetting, firewall rules, hybrid connectivity (VPN/Interconnect), Cloud Load Balancing, Certificate management, and Cloud DNS to ensure secure and efficient traffic flow.

Administer compute resources across Compute Engine, Cloud Run, and Cloud SQL.

Security & Governance

Implement and assist in the management of a robust security posture using IAM roles and permissions, ensuring the principle of least privilege across all projects.

Manage secrets and sensitive configurations using GCP Secret Manager.

Manage Cloud Armor for DDoS protection and Identity-Aware Proxy (IAP) for secure administrative access.

Utilize Security Command Center to proactively identify and remediate vulnerabilities.

Manage and assist in our ability to ensure the environment meets industry standards such as SOC2.

Operations & Reliability

Establish comprehensive monitoring and alerting frameworks using Google Cloud Observability.

Develop and test automated backup and disaster recovery strategies.

Perform regular system patching and image hardening.

Cost Management (FinOps)

Monitor cloud consumption and implement cost-saving measures (e.g., committed use discounts, right-sizing).

Establish billing alerts and resource labeling standards.

Migration & Data Orchestration (Priority Focus)

Legacy Migration: Lead the strategic migration of batch scheduling workloads from on-premises systems to GCP Composer / Apache Airflow.

DAG Development: Design and implement scalable, maintainable Directed Acyclic Graphs (DAGs) to automate complex data pipelines and batch jobs.

Workflow Optimization: Analyze legacy batch schedules to identify opportunities for parallelization, optimization, and modernization in the cloud.

Cutover Planning: Manage the risk and execution of "cutover" events, ensuring zero data loss and minimal downtime during the transition from on-prem to GCP.

Operational Requirements & Availability

Crucial Note on Availability: As this role is critical to the stability of our production environments, the successful candidate must be available for support during both standard business hours and non-business hours. This includes:

Participation in an on-call rotation.

Availability for emergency troubleshooting during weekends or overnight if a critical system failure occurs.

Scheduling maintenance windows and migration cutovers during off-peak hours.

Qualifications & Skills

Minimum Requirements:

Experience: 3–5+ years of professional experience managing production environments in Google Cloud Platform (GCP).

Migration Expertise: 3–5 years of proven experience supporting the migration of on-premises batch scheduling systems to GCP Composer or Apache Airflow.

IaC: Proven expertise with Terraform for provisioning cloud resources.

Containers: Strong proficiency with Docker and Kubernetes (K8s).

OS: Expert-level knowledge of Linux administration.

Networking: Deep understanding of TCP/IP, DNS, and Load Balancing.

Preferred Qualifications:

Certification: GCP Professional Cloud Architect or Professional Data Engineer.

CI/CD: Experience with GitHub Actions, GitLab CI, or Google Cloud Build.

Scripting: Proficiency in Python (specifically for Airflow/Composer DAG development).