Fullstack Developer (Backend with Devops and Python)

• Build and maintain Python backend services and recommendation APIs consumed by internal products, ensuring reliable performance, scalability, and maintainability.
• Design and maintain GitHub Actions CI/CD pipelines and reusable workflows, enabling frequent deployments and controlled, manually approved production releases.
• Own observability and operational reliability with Datadog dashboards, logs, monitors, and alerts; investigate incidents and implement sustainable fixes.
• Ensure pragmatic security, cost awareness, and compliance with corporate standards, working with platform, security, and other corporate stakeholders.
• Contribute to code reviews, technical planning, architecture decisions, runbooks, and knowledge sharing within the squad.
• Challenge over-engineered solutions, including AI-generated proposals, and favor the simplest design that safely meets business needs.
• Design, provision, and continuously improve Google Cloud infrastructure using Terraform, including Cloud Run, GKE, Cloud SQL/PostgreSQL, IAM, and networking.
• Lead the simplification of the platform.

Required key competencies and qualifications:

• Proven senior-level experience developing and operating backend services and cloud infrastructure in production, with strong individual ownership;
• Deep hands-on expertise in Google Cloud Platform (GCP), particularly Cloud Run, GKE, Cloud SQL/PostgreSQL, IAM, and networking;
• Strong Terraform knowledge, including modules, state management, infrastructure repository design, and safe refactoring; familiarity with Terragrunt;
• Advanced Python programming skills and practical experience developing and maintaining APIs and microservices;
• Hands-on experience with GitHub, GitHub Actions, reusable CI/CD workflows, secrets management, and production deployment controls;
• Experience with production observability, monitoring, incident response, and troubleshooting, preferably using Datadog;
• Excellent collaboration and communication skills, including working across engineering, Data Science, Data Engineering, and platform teams, with a strong documentation habit;
• Very good fluency in English (written and verbal).

Nice to have:

• Understanding of Vertex AI Pipelines / Kubeflow Pipelines (KFP), BigQuery, or dbt in data-intensive environments;
• Exposure to Go or FastAPI;
• Experience navigating security and compliance requirements in a large international organisation;