We are looking for a skilled and proactive DevOps Engineer to join our cutting-edge data platform team. In this role, you will be the backbone of our data infrastructure, ensuring its reliability, performance, and continuous optimization. You will work closely with a talented group of data and analytics engineers to build and maintain a world-class platform. The ideal candidate is a problem-solver who is passionate about infrastructure automation, cloud technologies, and the unique challenges of a data-intensive environment.

Key Responsibilities
Infrastructure as Code (IaC): Design, build, and manage our cloud data infrastructure on GCP using Terraform. Champion automation and IaC best practices.
Platform Reliability & Performance: Take ownership of the stability, performance, and quality of our data platform. Implement robust monitoring, alerting, and logging to proactively identify and resolve issues.
Optimization: Continuously analyze and optimize the platform for cost, performance, and scalability. Ensure our resources are utilized efficiently.
Collaboration: Work in tight collaboration with data and analytics engineers to support their needs, streamline deployment processes, and ensure a stable development environment.
Proactive Improvement: Be a proactive force for improvement. Identify bottlenecks, security vulnerabilities, and opportunities to enhance our systems and processes.
Stay Current: Keep up-to-date with the latest trends in cloud infrastructure, data engineering, and AI technologies. Advise the team on best practices and new tools.
Client Communication: Effectively communicate technical concepts and platform status to both technical and non-technical stakeholders, including clients in an international setting.

Must-Have Qualifications
Proven experience as a DevOps Engineer, Site Reliability Engineer (SRE), or similar role.
Strong hands-on experience with cloud platforms, specifically GCP (Google Cloud Platform).
Expert-level knowledge of Terraform for managing infrastructure as code.
Solid understanding of data infrastructure components (e.g., data warehousing, ETL pipelines, data lakes).
Demonstrated ability to improve the performance, stability, and quality of complex platforms.
Knowledge of monitoring and observability tools (e.g., Elementary, Prometheus, Grafana, Datadog).
Hands-on experience with data-specific tools like BigQuery, Airflow, or dbt.
A proactive, self-starting, and problem-solving mindset.
Advanced/fluent level of English is mandatory for this international project.

Nice-to-Have Qualifications
Experience with containerization and orchestration tools (e.g., Docker, Kubernetes).
Familiarity with CI/CD tools and practices (e.g., Jenkins, GitLab CI, GitHub Actions).
An interest in or experience with the infrastructure requirements for AI and machine learning (MLOps).

If you like it, just apply and good luck!
#LI-JM2