The Platform and Infrastructure Engineer is crucial in managing and enhancing cloud-based platforms, blending system administration, programming expertise, and a deep understanding of cloud services. This role encourages creative problem-solving and effective communication, as you’ll often need to articulate complex technical ideas in design discussions, making you a strong collaborator across teams.

Your role

• Design, build, and maintain scalable cloud platforms, supporting multiple tenants.
• Manage and maintain components of data analytics platforms.
• Lead architecture development initiatives and conduct experimental proof of concepts.
• Develop cloud-native solutions using Infrastructure as Code (IaC) approaches.
• Oversee platform observability, ensuring comprehensive monitoring and alerting systems are in place.

Offer

• Long-term freelance contracts
• Solid market rates depending on experience
• Access to top-notch projects

Requirements

• GCP Expertise: hands-on experience with Google Cloud Platform (GCP), including building platforms within GCP environments.
• Infrastructure as Code (IaC): Proficiency in Terraform, coupled with experience using Azure DevOps for CI/CD pipeline automation.
• Cloud Analytics: Familiarity with GCP’s public cloud analytics services, such as BigQuery, Dataproc, and related offerings.
• Managed GCP Services: Hands-on experience with services like Cloud Run, GKE (Google Kubernetes Engine), Vertex AI, etc.
• Observability Tools: Strong experience with monitoring, logging, and alerting systems to ensure platform stability.
• Kubernetes Management: Extensive knowledge of deploying and managing Kubernetes applications, especially within GCP.
• System Administration: Proficiency in Linux system administration and Bash scripting.
• Programming: Strong programming skills, with a preference for Python and Golang.
• Security: Expertise in secure authentication methods and encrypted workloads (OIDC, KMS, SSL/TLS, etc.).

Nice to have:

• Large-Scale Systems: Experience building large-scale, secure cloud applications.
• Open-Source Contributions: Participation in open-source projects is a plus.
• Distributed Systems: Knowledge of distributed cloud computing and storage within GCP.
• Kubernetes Optimization: Experience with optimizing Kubernetes clusters, particularly within GKE.
• Automation-First Mindset: A commitment to automating processes wherever possible for increased efficiency and scalability.