GCP Cloud Engineer

About this role

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).