Pax Helm DevOps Engineer
San Francisco, CA • devops@gmail.com • +1 3333-5555
Profile Summary
- DevOps Engineer with 6 years of experience supporting high-traffic e-commerce systems, logistics automation platforms, and internal developer infrastructure, specializing in cloud-native reliability, pipeline automation, and scalable service delivery.
- Solid technical background across infrastructure-as-code (Terraform, Pulumi), container platforms (Kubernetes, ECS), CI/CD operations (GitHub Actions, GitLab CI, Jenkins), observability stacks (Prometheus, Grafana, ELK), and cloud ecosystems (AWS, Azure) with strong scripting fundamentals in Python and Bash.
- Well-versed in container lifecycle automation, performance tuning, service deployment patterns, network configuration, secrets management, and environment consistency, using repeatable IaC workflows, GitOps models, and automated release strategies such as canary and blue-green rollouts.
- Collaborative partner working closely with Backend, Data, and Security teams in Agile environments to plan deployments, resolve integration issues, conduct incident reviews, and support architectural decisions for distributed systems.
Technical Skills
- Cloud Platforms:
- AWS (EKS, ECS, Lambda, RDS, SQS, CloudWatch), Azure (AKS, Storage, Key Vault)
- Infrastructure as Code:
- Terraform, Pulumi, CloudFormation, Helm, Kustomize
- Containers & Orchestration:
- Docker, Kubernetes, ECS, AKS
- CI/CD & Automation:
- GitHub Actions, GitLab CI, Jenkins, ArgoCD
- Scripting & Languages:
- Python, Bash, Go (basic)
- Monitoring & Logging:
- Prometheus, Grafana, ELK Stack, Loki, Jaeger, CloudWatch
- Networking & Security:
- VPC, subnets, ALB/NLB, IAM, TLS, security groups, OIDC, Vault
- Version Control & Tooling:
- Git, GitHub, GitLab, ArgoCD, Artifactory
Education
University of Washington
B.S. in Computer Science
Work Experience
Shopify
DevOps Engineer
- Delivered a fully declarative deployment model using Terraform, Kubernetes, Helm, and ArgoCD, designing modular IaC patterns with parameterized state separation, immutable environment baselines, and GitOps reconciliation loops, slashing config drift events by 95% and stabilizing release pipelines for 30+ microservices.
- Engineered a high-throughput CI/CD system using GitHub Actions, GitLab CI, and container layer caching, optimizing build graphs, dependency hydration, and test distribution across parallel runners using dynamic job fans, reducing build times from 14m to 5m (~64%) and doubling deployment throughput during peak hours.
- Tuned Kubernetes workload performance using HPA/VPA policies, pod disruption budgets, resource quantization, and priority classes, combined with Prometheus-driven saturation signals to right-size CPU/memory allocations and trim cluster footprint by 28% while maintaining p99 latency under 180ms during holiday load.
- Implemented progressive delivery via canary batches, header-based routing, and SLI-driven rollback gates using Envoy and OpenTelemetry, enabling automated rollback within 90 seconds when early-stage degradation exceeded error-rate budgets.
- Built a full observability layer using Prometheus, Alertmanager, Loki, Grafana, and Jaeger, instrumenting services with OpenTelemetry traces, RED/USE dashboards, and log correlation indexes, cutting mean diagnostic time from 45m to 8m.
NexTrade Digital
DevOps Engineer
- Developed AWS infrastructure using Terraform, CloudFormation, and ECS, implementing reusable network modules (VPC layout, ALB routing maps, service mesh rules, RDS failover configs) that cut environment provisioning from hours to under 20 minutes.
- Created deployment pipelines using Jenkins and GitHub Actions, integrating artifact fingerprinting, pre-deploy smoke jobs, sidecar scanning, and transaction-level health probes, improving deployment reliability by 38% and reducing manual intervention across release cycles.
- Built shell scripts and custom Python/Bash automation for config synchronization, log extraction, secret hydration, and bootstrap routines, eliminating 12-15 hours per sprint of repetitive operational work while raising onboarding speed for new engineers by 50%.
