Alex is available for hire
Hire AlexAlex Zhang
Verified Expert in Engineering
DevOps Engineer and AWS Developer
Toronto, ON, Canada
Toptal member since October 4, 2021
Bio
Alex is a DevOps engineer with over 10 years of experience in cloud infrastructure, infrastructure as code (IaC), containerization, CI/CD, monitoring and observability, configuration management, and shell scripting. His technologies include AWS, Terraform, Terragrunt, Kubernetes, Argo CD, GitHub, GitLab, Datadog, Prometheus, Grafana, Ansible, Python, and Linux. Alex learns fast and continuously welcomes a challenge.
Portfolio
Furniture
Amazon Web Services (AWS), DevOps, Infrastructure as Code (IaC), Terraform...
Hub International
Kubernetes, Terraform, Amazon Web Services (AWS)
Sweetgreen
Terraform, Amazon Web Services (AWS), CI/CD Pipelines, Node.js, GitHub...
Experience
- Linux - 10 years
- Python - 10 years
- Amazon Web Services (AWS) - 10 years
- Kubernetes - 8 years
- Terraform - 5 years
- GitHub Actions - 3 years
- Argo CD - 3 years
- Databricks - 3 years
Availability
Full-time
Preferred Environment
Amazon Web Services (AWS), Terraform, Kubernetes, Python, Linux, GitHub, Datadog, Databricks
The most amazing...
...project I've implemented is an ML operations project on AWS using Kubeflow for model deployment.
Work Experience
Senior Infrastructure Engineer
2022 - 2024
Furniture
- Designed and managed AWS infrastructure that ensured scalability, availability, and security, supporting millions of users.
- Built and maintained infrastructure as code using Terraform, Terragrunt, AWS CloudFormation, and AWS CDK, automating the provisioning and lifecycle of AWS resources.
- Led efforts to deploy and maintain Kubernetes clusters, optimizing for resource efficiency, scalability, and high availability.
- Developed and maintained a robust CI/CD pipeline with GitHub Actions and Argo CD, enabling seamless deployment of containerized microservices to Kubernetes clusters.
- Created and enhanced monitoring and alerting solutions with Datadog, AWS CloudWatch, and other tools, proactively identifying and resolving performance issues.
- Partnered with security teams to meet security standards and comply with regulations such as CIS and SOC 2.
- Supported the data engineering team by designing and implementing a scalable, secure data analytics and processing platform on Databricks.
- Collaborated closely with development, QA, and other teams to optimize CI/CD pipelines, accelerate deployments, and ensure code quality.
- Produced and maintained detailed documentation of infrastructure, workflows, and configurations to support knowledge sharing and best practices.
- Diagnosed and resolved complex system issues, troubleshooted network problems, and provided technical support as needed.
Technologies: Amazon Web Services (AWS), DevOps, Infrastructure as Code (IaC), Terraform, Terragrunt, CI/CD Pipelines, GitHub Actions, Datadog, Python, Linux, Databricks
Kubernetes and Terraform Specialist
2022 - 2022
Hub International
- Deployed and managed the production-grade infrastructure, including the network topology, orchestration tools, databases, caches, load balancers, CI/CD pipeline, monitoring, alerting, log aggregation, etc.
- Defined and managed infrastructure as code using Terraform, Terragrunt, and Gruntwork Service Catalog; also developed custom Terraform modules to meet the company's needs.
- Moved services from AWS ECS (an old AWS account) to AWS EKS without downtime.
Technologies: Kubernetes, Terraform, Amazon Web Services (AWS)
Site Reliability Engineer
2022 - 2022
Sweetgreen
- Built, tested, troubleshot, and maintained IaC code for software systems and infrastructure.
- Promoted strong design principles as they relate to scalability, disposable resources, automation, loose coupling, databases, removing single points of failure, cache, cost, and security.
- Worked closely with lead engineers, software engineering managers and principals, they champion architectural decisions that facilitate the work of their teams and our business as a whole.
Technologies: Terraform, Amazon Web Services (AWS), CI/CD Pipelines, Node.js, GitHub, AWS Fargate, AWS Lambda, Docker, Amazon API Gateway, Terragrunt, Amazon Elastic Container Service (ECS), CircleCI, Gruntwork
AWS Cloud Infrastructure Engineer
2021 - 2021
Alteryx
- Used the latest DevOps and cloud deployment techniques—Amazon EKS and AWS ECR, RDS, EC2, and S3—to create and integrate innovative new products into the company's platform.
- Built and deployed infrastructure as code using Terraform.
- Designed and tested high-security, leakproof back-end infrastructure to host multitenant and single-tenant deployments.
- Provided support to small-but-mighty engineering teams that utilized CI/CD principles in GitLab and Argo CD.
- Performed standard database administration duties using RDS, PostgreSQL, Snowflake, and other ANSI SQL platforms.
Technologies: Terraform, Docker, Kubernetes, Helm, Argo CD, Vault, Bash, Bash Script, Amazon EKS, Amazon Web Services (AWS), DevOps, Cloud Deployment, Amazon Elastic Container Registry (ECR), Amazon RDS, Amazon EC2, Amazon S3 (AWS S3), Infrastructure as Code (IaC), Cloud Infrastructure, CI/CD Pipelines, GitLab CI/CD, Database Administration (DBA), PostgreSQL, Snowflake, DevOps Engineer
Senior DevOps Engineer
2018 - 2021
Pro Notary LLC
- Designed, improved, and monitored the cloud infrastructure on AWS and Azure.
- Developed and managed the infrastructure as code using Terraform.
- Created and maintained the CI/CD pipelines using Azure Pipelines, Docker, Kubernetes, Helm, and Argo CD.
- Set up and maintained monitoring and observability systems using ELK (Elastic Stack).
- Worked on configuration management and application deployment using Ansible, Python, and Bash.
Technologies: Terraform, Ansible, Kubernetes, Docker, Argo CD, Bash, Infrastructure as Code (IaC), Helm, CI/CD Pipelines, DevOps, Bash Script, Azure DevOps, Cloud Infrastructure, Configuration Management, DevOps Engineer, Python, Amazon Web Services (AWS), Amazon EKS
DevOps Engineer
2015 - 2018
Neusoft
- Developed microservices and REST APIs using Python Django.
- Built and deployed Docker containers to break up a monolithic app into microservices, which improved the developer workflow and increased scalability.
- Automated the deployment, scaled, and managed the Docker containers using Kubernetes.
- Designed, improved, and monitored the cloud infrastructure on AWS, including IAM, VPC, EC2, S3, RDS, ElastiCache, SNS, SQS, ECR, and EKS.
- Created and maintained the CI/CD pipelines using Bitbucket, Jenkins, and CircleCI.
- Set up and maintained the monitoring and observability systems using ELK (Elastic Stack).
Technologies: Terraform, Docker, Kubernetes, Jenkins, CircleCI, Microservices, CI/CD Pipelines, Amazon Web Services (AWS), Bash Script, Amazon EKS, Cloud Infrastructure, AWS IAM, Amazon EC2, Amazon Virtual Private Cloud (VPC), Amazon S3 (AWS S3), Amazon RDS, Amazon Elastic Container Registry (ECR), DevOps, DevOps Engineer
Experience
MLOps Platform on AWS using Kubeflow for Model Deployment
The project mainly focused on building and deploying the marketing attribution model on AWS using Kubeflow pipelines in Python.
The code of an ML model, ML pipeline, infrastructure, and dependencies (all of which are stored and versioned in Git), as well as a dataset from a centralized feature store, are compiled into the model by ML Orchestrator to generate logs, metrics, alerts, and data for storage and analysis.
Continuous delivery and experimentation workflows are dynamically integrated. This setup allows us to use the same pipeline to initiate experiments manually and automatically. These are triggered from Git hooks and CI/CD tools for continuous integration and deployment.
The code of an ML model, ML pipeline, infrastructure, and dependencies (all of which are stored and versioned in Git), as well as a dataset from a centralized feature store, are compiled into the model by ML Orchestrator to generate logs, metrics, alerts, and data for storage and analysis.
Continuous delivery and experimentation workflows are dynamically integrated. This setup allows us to use the same pipeline to initiate experiments manually and automatically. These are triggered from Git hooks and CI/CD tools for continuous integration and deployment.
Migrating AWS Infrastructure Using Gruntwork Reference Architecture
DELIVERABLES
• Deployed and managed production-grade infrastructure, including the network topology, orchestration tools, databases, caches, load balancers, CI/CD pipeline, monitoring, alerting, log aggregation, etc.
• Defined and managed the infrastructure as code using Terraform, Terragrunt, and Gruntwork Service Catalog; also developed custom Terraform modules to meet the company's needs.
• Moved services from AWS ECS to AWS EKS without any downtime.
• Deployed and managed production-grade infrastructure, including the network topology, orchestration tools, databases, caches, load balancers, CI/CD pipeline, monitoring, alerting, log aggregation, etc.
• Defined and managed the infrastructure as code using Terraform, Terragrunt, and Gruntwork Service Catalog; also developed custom Terraform modules to meet the company's needs.
• Moved services from AWS ECS to AWS EKS without any downtime.
Education
2011 - 2015
Bachelor's Degree in Telecommunications Engineering
Shenyang Institute of Engineering - Shenyang, Liaoning, China
Certifications
MAY 2024 - MAY 2027
AWS Certified Solutions Architect - Professional
Amazon Web Services
MAY 2024 - MAY 2027
AWS Certified Machine Learning - Specialty
Amazon Web Services
APRIL 2024 - APRIL 2025
Databricks Platform Administrator
Databricks
JULY 2021 - JULY 2024
Certified Kubernetes Administrator (CKA)
The Linux Foundation
JUNE 2021 - PRESENT
Certified Jenkins Engineer
Jenkins
MAY 2021 - MAY 2023
HashiCorp Certified: Terraform Associate
HashiCorp
APRIL 2021 - APRIL 2023
Docker Certified Associate
Mirantis, Inc.
Skills
Libraries/APIs
Terragrunt, Node.js
Tools
Terraform, Jenkins, Amazon EKS, Amazon Elastic Container Registry (ECR), AWS IAM, Amazon Virtual Private Cloud (VPC), Ansible, Helm, CircleCI, GitLab CI/CD, Vault, GitHub, AWS Fargate, Amazon Elastic Container Service (ECS), Grafana
Languages
Bash, Bash Script, Python, Snowflake
Paradigms
DevOps, Microservices, Azure DevOps
Platforms
Docker, Kubernetes, Linux, Amazon Web Services (AWS), Amazon EC2, Databricks, AWS Lambda, Kubeflow
Storage
Cloud Deployment, Amazon S3 (AWS S3), PostgreSQL, Datadog, Database Administration (DBA)
Frameworks
Django
Other
Argo CD, Amazon RDS, Cloud Infrastructure, DevOps Engineer, GitHub Actions, Infrastructure as Code (IaC), CI/CD Pipelines, Configuration Management, Amazon API Gateway, Gruntwork, Computer Science, Amazon Machine Learning, Prometheus
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