Why This Role Stands Out
This on-site Google Cloud Platform Engineer role offers significant growth potential within a reputable US-based tech company known for its innovation. You'll thrive here if you possess strong GCP, Terraform, and containerization skills, and are eager to contribute to cutting-edge projects. Apply now to join a dynamic team and advance your cloud engineering career.
Quick Overview
Job Description
K&K Global Talent Solutions Inc. is an international recruiting agency that has been providing technical resources in the Canada and the USA region since 1993.
This position is with one of our clients in USA, who is actively hiring candidates to expand their teams.
Role:- Google Cloud Platform Cloud Engineer
Location:- Sunnyvale, CA (onsite)
Fulltime
Job Description
Must Have Technical/Functional Skills:
Compute Engine; Cloud Run; App Engine; Cloud Functions; Cloud Storage; Cloud SQL; Spanner; BigQuery; Dataflow; Dataproc; Composer; Pub/Sub; Terraform; Helm; Cloud Build; Artifact Registry; Git (GitHub/GitLab); Docker; Python; Go; Bash; SQL; Kubernetes fundamentals; VPC; subnets; Cloud NAT; Load Balancing; Private Service Connect; Cloud Armor (WAF); VPN/Interconnect; IAP; VPC Service Controls; Org Policies; KMS; Secret Manager; IAM; Cloud Monitoring; Cloud Logging; Error Reporting; Trace; Profiler
Roles & Responsibilities:
• Architect and deliver Google Cloud Platform workloads using Compute Engine, GKE, Cloud Run, Cloud Storage, Cloud SQL/Spanner, Pub/Sub.
• Build infrastructure as code and CI/CD (Terraform, Cloud Build, Git) with environment promotion and guardrails.
• Implement identity and security controls (IAM, service accounts, Secrets Manager, KMS, org policies, VPC Service Controls).
• Design scalable networking (VPCs, subnets, NAT, load balancers, Private Service Connect) and interconnectivity.
• Establish observability and SRE practices (Cloud Monitoring, Logging, Error Reporting; SLIs/SLOs, alerting, runbooks).
• Develop data platforms and pipelines with BigQuery, Dataflow/Beam, Composer/Airflow, Dataproc; batch and streaming.
• Automate operations with Cloud Functions/Run and APIs; drive reliability, performance, and cost optimization.
• Lead incident response and postmortems; mentor engineers and document standards.
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