Senior Cloud Platform Engineer

TGS; Weybridge; On-site; GBP 70,000 - 100,000; Full time

Job summary

A leading company in the energy sector is seeking a Senior Cloud Platform Engineer to drive the technical vision for its multi-cloud platform. This role involves designing and maintaining core cloud components, primarily on GCP, with a focus on Kubernetes, while fostering a developer-centric environment. The ideal candidate will have advanced knowledge in cloud technologies and a passion for empowering development teams to utilize cloud solutions effectively.

Qualifications

• Advanced knowledge and hands-on experience with GCP services.
• Advanced knowledge and experience with Kubernetes, specifically GKE.
• Advanced proficiency in Python and Go.

Responsibilities

• Lead the design, development, and implementation of core cloud platform components.
• Drive the adoption of the cloud platform across development teams.
• Implement robust monitoring, logging, security, and automation for the cloud platform.

Skills

Advanced GCP Knowledge

Deep Kubernetes Expertise

Expert Level Infrastructure as Code

Multi-Cloud Experience

Cloud-Native Architecture

Cloud-Native Observability

Identity and Access Management (IAM)

Programming Skills

DevOps/GitOps

Communication and Influence

Job description

TGS provides scientific data and intelligence to companies active in the energy sector. In addition to a global, extensive and diverse energy data library, TGS offers specialized services such as advanced processing and analytics alongside cloud-based data applications and solutions.

We are seeking a highly motivated and experienced Senior Cloud Platform Engineer to our Research & Technology - Architecture team. In this position you will play a pivotal in driving and defining the technical vision and roadmap for the company's multi-cloud platform (GCP, AWS, and Azure). This position involves designing, building, and maintaining core cloud platform components, with a primary focus on Kubernetes (specifically GKE) and fostering a developer-centric platform environment.

The Senior Cloud Platform Engineer will champion the adoption and effective utilization of the cloud platform by development teams across the organization, ensuring its reliability, scalability, security, and cost-effectiveness through robust operational practices. This role also contributes to the company's overall cloud strategy and requires staying abreast of emerging cloud technologies.

Key Responsibilities

• Design and Build: Lead the design, development, and implementation of core cloud platform components, primarily on GCP, with a focus on Kubernetes (GKE) and a robust developer platform.

• Developer Empowerment: Develop and champion a developer-centric platform and software catalogue, promoting self-service capabilities and ease of use for all development teams. This includes building tools and workflows to streamline the development lifecycle.

• Platform Adoption: Drive the adoption of the cloud platform across development teams. This includes providing onboarding, training, documentation, and ongoing support to ensure successful integration and utilization.

• Operational Excellence: Implement robust monitoring, logging, security, and automation (using DevOps/GitOps principles) for the cloud platform to ensure high availability, reliability, performance, and cost-efficiency.

• Technology Leadership: Proactively research, evaluate, and recommend new cloud technologies and best practices. Contribute to the company's cloud strategy, including cost optimisation and future roadmap planning.

• Collaboration: Work closely with IT infrastructure, security, and operations teams to ensure the platform meets the needs of the business and adheres to security and compliance standards.

Required Competencies

• Advanced GCP Knowledge: Advanced knowledge and hands-on experience with Google Cloud Platform (GCP) services.

• Deep Kubernetes Expertise: Advanced knowledge and experience with Kubernetes, specifically Google Kubernetes Engine (GKE). This includes deployment, management, scaling, and troubleshooting for Linux and Windows node pools. Ability to design and implement API extensions (CRD) and controllers.

• Expert Level Infrastructure as Code: Advanced knowledge of Terraform/OpenTofu, including module authoring and publication. Knowledge of Kubernetes-based resource orchestration (e.g., KCC, Crossplane).

• Multi-Cloud Experience: Strong understanding of AWS and Azure cloud platforms.

• Cloud-Native Architecture: Proven capability to design and implement cloud-native solutions on GCP, leveraging best practices for scalability, resilience, and maintainability.

• Cloud-Native Observability: Experience with implementing and maintaining observability solutions on and for cloud-native platforms (e.g., Prometheus, Grafana, Loki, Tempo, Mimir - potentially the LGTM stack) and supporting developer teams to export and leverage metrics, logs, traces, and profiles for their applications.

• Identity and Access Management (IAM): Experience with cloud identity providers like Microsoft Entra ID, Okta, or Google Workspace.

• Programming Skills: Advanced proficiency in Python and Go.

• DevOps/GitOps: Strong understanding and practical experience with DevOps and GitOps practices, including CI/CD, infrastructure-as-code, and configuration management tools (e.g., Azure DevOps, GitLab CI/CD, GitHub Actions, Argo CD, Flux).

• Communication and Influence: Excellent communication, documentation, and interpersonal skills. Ability to inspire, engage, and influence developers to adopt new technologies and practices.

Desired Competencies

• Data Pipeline Frameworks: Experience with Kubernetes-based data pipeline frameworks such as Apache Airflow, GCP Cloud Composer, or similar workflow orchestration tools (e.g., Argo Workflows, Kubeflow Pipelines). (Note: BentoML is typically for ML model serving, might need clarification if data pipelines are the focus).

• AI/Generative AI Platform Integration: Experience integrating AI/ML platforms (e.g., Vertex AI, Sagemaker, Azure ML) and Gen AI services into cloud infrastructure, including deployment patterns for models and managing associated resources.

• MLOps Practices: Familiarity with MLOps principles and tools for automating the machine learning lifecycle on cloud platforms.

• FinOps/Cloud Cost Management: Experience with cloud cost monitoring, analysis, and optimization strategies and tools.

• Security Best Practices: Deeper knowledge of cloud security principles, threat modeling, and implementing security controls within cloud platforms and CI/CD pipelines.

• Networking: Understanding of advanced cloud networking concepts, including VPC design, peering, load balancing, and DNS in a multi-cloud context.

Location: Weybridge or Oslo

If you are passionate about cloud technology and developer platforms, and ready to help evolve our multi-cloud strategy, please submit your application by June 11, 2025.