DevOps Tech Lead/Architect

We need a DevOps Tech Lead to form an opinion on the roadmap of overall improvements within the account and pushing it through.
Main technical focus is: Automation scripting, Python and environment provisioning.

The client is in California. To have at least 2–3 hr overlap, the working time should extend at least into 7-8 PM CET.

Details on tech stack:
Deep DevOps expertize is mandatory
Automation scripting (Bash, etc.)
Python mandatory
Monitoring and Observability: Familiarity with tools like Looker for creating dashboards and monitoring cloud resources is priority - Grafana, Loki, Prometheus, etc.
Cloud Platform Knowledge: Proficiency in Google Cloud Platform (GCP) is essential, as many discussions revolve around GCP projects, services, and resources.
Infrastructure as Code: Understanding of Terraform and Terraform Enterprise (TFE) is crucial, as there are multiple mentions of Terraform-related issues and configurations.
Identity and Access Management (IAM): Knowledge of GCP IAM, including service accounts, roles, and permissions, is frequently needed to address user queries.
DevOps and CI/CD: Familiarity with DevOps practices and CI/CD pipelines, including tools like GitHub Actions, is important for troubleshooting deployment issues.
Networking and Security: Understanding of cloud networking, firewall rules, and security best practices is necessary to assist with configuration and compliance issues.
Database Management: Knowledge of various database types, including SQL and NoSQL, is helpful for addressing data-related queries.
Scripting and Automation: Proficiency in scripting languages like Python or Bash is valuable for automating tasks and solving user problems efficiently.
Cost Optimization: Understanding of FinOps principles and cloud cost management is important, as there are discussions about reducing wasteful cloud spend.
Documentation and Knowledge Management: Skills in creating and maintaining technical documentation, such as ADRs (Architecture Decision Records), are valuable for improving the overall knowledge base.
Collaboration Tools: Proficiency in using collaboration platforms like Slack, Jira, and Confluence is essential for effective communication and problem-solving.
Containerization: Knowledge of container technologies, particularly in the context of GCP, is helpful for addressing deployment and scaling issues.

Requirements to the candidate:
Deep DevOps Expertise with experience in architecture, with and ability to participate in this area
Bash
Python
Flask / SQLAlchemy
Helm
Oracle DB SQL
Groovy and Jenkins shared pipeline libraries
Good knowledge of Linux & networks
Terraform
Docker, Kubernetes
Jenkins
Grafana, Loki
 

Candidate responsibilities
Work with the customer to identify project opportunities
Work with the team to identify their pain: risks, issues and potential improvements
Form strong opinion on the measures which can solve the issues outlined above
Communicate the opinion to the customer and all the stakeholders
Build a roadmap of changes and lead the team along it