Senior Devops / Platform Engineer

Strategy Big Data; A distancia; EUR 60.000 - 90.000; Jornada completa

Descripción de la vacante

A cloud technology firm is seeking a Senior DevOps / Platform Engineer based in Spain. The role involves designing, automating, and operating cloud-native infrastructure across AWS and GCP. Responsibilities include managing Kubernetes clusters, implementing CI/CD workflows, and collaborating with engineering teams. This position offers real ownership, and opportunities for significant impact with competitive salary and fully remote work. Join a dynamic team and shape the platform's future while working with cutting-edge technologies.

Servicios

Competitive salary package

Fully remote work with flexible hours

23 days of vacation + Spanish public holidays

Continuous learning opportunities

Mentoring and growth potential

Formación

• 5+ years of experience in a DevOps, SRE, or Platform Engineer role.
• Strong hands-on experience with Kubernetes at scale (GKE, EKS).
• Expert knowledge of Terraform and Infrastructure as Code.

Responsabilidades

• Design, build, and maintain multi-cloud infrastructure on AWS and GCP.
• Lead infrastructure modernization and cloud migration initiatives.
• Implement cost optimization strategies across cloud providers.

Conocimientos

Kubernetes management

Terraform and Infrastructure as Code

Multi-cloud experience

CI/CD and GitOps

Docker and Helm expertise

Scripting in Python and Bash

Herramientas

Prometheus

Grafana

MongoDB

ElasticSearch

ArgoCD

Descripción del empleo

About Us

We build and operate a fully-automated Speech Analytics SaaS platform running on Kubernetes across AWS and GCP. Our infrastructure processes ~160,000 hours of audio monthly with 99%+ uptime SLA, serving enterprise customers with mission-critical analytics needs.

Our platform is built on modern, cloud-native technology: Kubernetes, Argo ecosystem, MongoDB, ElasticSearch, and 100% Terraform-driven Infrastructure as Code. We auto-scale from dozens to over 1,000 kubernetes nodes based on demand.

Beyond our core SaaS product, we deliver managed solutions (Autopilot and Copilot platforms) and build AI-based services packaged as containerized, Terraform-ready modules for seamless integration into customer cloud environments (AWS, GCP, Azure).

We're a team that values strong engineering practices, automation-first mindset, and operational excellence.

About the Role

We're looking for a Senior DevOps / Platform Engineer to help design, automate, and operate our cloud-native platform. You'll work across AWS and GCP, manage Kubernetes at scale, implement highly-automated CI/CD workflows, and collaborate with engineering teams to ensure reliable delivery of SaaS features and AI-driven products.

What Makes This Role Unique

Real ownership and autonomy – you'll be a key technical decision-maker.

Work directly with leadership on platform strategy.

Hands‑on with cutting‑edge cloud‑native and AI/ML workloads.

Opportunity to lead a major AWS / GCP migration to optimize costs and performance.

This role is ideal for someone who thrives in high‑automation environments, enjoys solving complex platform challenges, and wants a visible impact on products used by enterprise customers.

Location

Fully remote (Spain‑based)

Key Responsibilities

• Design, build, and maintain multi‑cloud infrastructure on AWS and GCP.
• Operate and optimize Kubernetes clusters (GKE, EKS) at scale (up to ~1K nodes).
• Lead infrastructure modernization and cloud migration initiatives.
• Implement cost optimization strategies across cloud providers.
• Manage Argo Workflows and ArgoCD for GitOps‑based deployments.
• Build and maintain end‑to‑end Infrastructure as Code with Terraform (modularized, reusable, multi‑cloud).
• Develop internal automation tooling and scripts (Python, Bash, Go).
• Implement zero‑downtime deployment strategies.
• Deploy and manage production MongoDB, ElasticSearch, and other core services.
• Package and deploy workloads using Helm, Docker, and GitOps pipelines.
• Ensure 99%+ uptime SLA through robust monitoring and incident response.
• Support delivery of AI containerized solutions ready for customer environments.
• Build comprehensive observability across all platform components.
• Implement security best practices and compliance requirements.
• Drive post‑incident reviews and continuous improvement.

Requirements

• Must Have

• 5+ years as a DevOps, SRE, or Platform Engineer in production environments.
• Strong hands‑on Kubernetes experience (GKE and/or EKS) managing clusters at scale.
• Expert‑level Terraform and Infrastructure as Code workflows.
• Multi‑cloud experience with both AWS and GCP.
• Proven experience with CI/CD, GitOps, ArgoCD, Argo Workflows.
• Solid Docker and Helm expertise for containerized deployments.
• Strong scripting/programming skills in Python and Bash.
• Experience running production‑grade, scalable, and secure cloud systems.
• Comfortable with incident response and on‑call responsibilities.

• Nice to Have

• Programming for tooling development (Python, bash, Go, ...).
• Experience with observability stacks (Prometheus, Grafana, Elastic, OpenTelemetry).
• Hands‑on with AI/ML workloads in containerized environments.
• MongoDB and ElasticSearch operations at scale.
• Experience with cost optimization strategies in cloud environments.
• Contributions to open‑source DevOps/platform projects.
• AWS/GCP certifications.

Compensation & Benefits

• Competitive salary package.
• Fully remote work with flexible hours.
• 23 days of vacation + Spanish public holidays.
• Growth & Impact: Real ownership – your decisions shape the platform's future.
• Work directly with leadership on technical strategy.
• Continuous learning with modern cloud‑native, DevOps, and AI tooling.
• Opportunity to mentor and grow the team as we scale.
• Visible impact on products used by enterprise customers.
• Engineering‑driven culture that values automation and best practices.
• Async‑first communication (we respect work‑life balance).
• Blameless post‑mortems and learning from incidents.
• Regular team knowledge‑sharing sessions and open cooperation.

Interview Process

• Initial call (30 min).
• Technical interview (60 min).
• Final interview.

Timeline

Typically 2–3 weeks from application to offer.

How to Apply

Apply here or send your CV and a brief note about what excites you about this role to ******.