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
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Design, build, and maintain scalable cloud infrastructure using Infrastructure as Code (IaC), primarily via Terraform.
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Deploy and manage optimized Compute Engine’s, Google Kubernetes Engine (GKE) clusters, serverless options like Cloud Run or Cloud Functions.
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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.
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Administer compute resources across Compute Engine, Cloud Run, and Cloud SQL.
Security & Governance
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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.
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Manage secrets and sensitive configurations using GCP Secret Manager.
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Manage Cloud Armor for DDoS protection and Identity-Aware Proxy (IAP) for secure administrative access.
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Utilize Security Command Center to proactively identify and remediate vulnerabilities.
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Manage and assist in our ability to ensure the environment meets industry standards such as SOC2.
Operations & Reliability
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Establish comprehensive monitoring and alerting frameworks using Google Cloud Observability.
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Develop and test automated backup and disaster recovery strategies.
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Perform regular system patching and image hardening.
Cost Management (FinOps)
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Monitor cloud consumption and implement cost-saving measures (e.g., committed use discounts, right-sizing).
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Establish billing alerts and resource labeling standards.
Migration & Data Orchestration (Priority Focus)
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Legacy Migration: Lead the strategic migration of batch scheduling workloads from on-premises systems to GCP Composer / Apache Airflow.
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DAG Development: Design and implement scalable, maintainable Directed Acyclic Graphs (DAGs) to automate complex data pipelines and batch jobs.
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Workflow Optimization: Analyze legacy batch schedules to identify opportunities for parallelization, optimization, and modernization in the cloud.
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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:
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Participation in an on-call rotation.
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Availability for emergency troubleshooting during weekends or overnight if a critical system failure occurs.
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Scheduling maintenance windows and migration cutovers during off-peak hours.
Qualifications & Skills
Minimum Requirements:
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Experience: 3–5+ years of professional experience managing production environments in Google Cloud Platform (GCP).
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Migration Expertise: 3–5 years of proven experience supporting the migration of on-premises batch scheduling systems to GCP Composer or Apache Airflow.
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IaC: Proven expertise with Terraform for provisioning cloud resources.
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Containers: Strong proficiency with Docker and Kubernetes (K8s).
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OS: Expert-level knowledge of Linux administration.
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Networking: Deep understanding of TCP/IP, DNS, and Load Balancing.
Preferred Qualifications:
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Certification: GCP Professional Cloud Architect or Professional Data Engineer.
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CI/CD: Experience with GitHub Actions, GitLab CI, or Google Cloud Build.
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Scripting: Proficiency in Python (specifically for Airflow/Composer DAG development).
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