arsys
IT sector
StaffDevOPSEngineer(f/m/d)
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“Staff DevOPS Engineer (f/m/d) at arsys. Skills: Platform Operations, L2/L3 Application Support, Stakeholder Coordination, Agile Collaboration. Shape, deploy, and maintain cloud Big Data platform. Take full responsibility for operation”
What You'll Achieve.
evolve our platforms; empower our customers; support data-driven decision-making
Industry & Context.
problem-solving attitude; solve challenges independently
What They're Looking For.
Must Have
Minimum 5+ years of proven experience in Operations, System Administration, or infrastructure-focused DevOps roles, Confident, high-level handling of Linux systems, environments, and server recovery processes, Deep practical experience with infrastructure-as-code and deployment automation technologies, knowledge and hands-on experience with Kubernetes and containerization technologies, Practical experience with networking concepts and technologies, High degree of autonomy to take ownership of an issue and solve challenges independently, Good English skills (written and spoken)
Nice to Have
Familiarity or practical experience with tools such as Trino, Hive, Airflow, OpenShift, Prometheus, or Grafana, Practical experience with Python programming and related frameworks, Linux Foundation certifications regarding Kubernetes (e.g., CKA/CKAD), Experience with highly secure environments (e.g., handling sensitive data or regulated sectors)
What You'll Do.
and maintain cloud Big Data platform
Take full responsibility for operation
Serve as first point of contact
Troubleshoot process failures
Investigate data pipeline failures
Optimize platform performance
Discuss and gather requirements
Implement additional platform services
Participate actively in team processes
Develop operational process definitions
Develop platform optimization setups
Take over system responsibilities
How You'll Work.
Team & Collaboration
Close coordination with internal stakeholders; Agile Collaboration; working within 2-week sprints; keeping the team aligned; shares knowledge
Communication Scope
Good English skills (written and spoken); collaborate effectively across multidisciplinary and international teams
Full Job Description
We offer you the opportunity to join the leading Spanish company in the IT sector, with more than 25 years of experience and one of the most solid track records as a provider of technological solutions for companies. We are a growing company with more than 400 employees and offices in Logroño, Madrid, Barcelona, Seville, Bilbao and Valencia. Since August 2013, we have been part of the IONOS Group, Europe's leading digitalisation partner for small and medium-sized companies. In short, we are a multicultural team that’s passionate about technology, bringing our professional experience from over a dozen countries: Germany, Argentina, Spain, the United States, France, the Philippines, Italy, Poland, Portugal, the United Kingdom, Romania... Our department’s vision is to build a Data-Driven IONOS Group. Our mission is to connect AI and BI, evolve our platforms, and empower our customers. As the central provider of the BI platform for Corporate, CTO topics, and state-of-the-art AI solutions, we support data-driven decision-making all across the IONOS Group. Currently, we are building our new cloud Big Data platform completely based on the IONOS cloud infrastructure. This means you will work with up-to-date, non-commercial technologies and have the unique opportunity to operate on our own internal cloud ecosystem, completely independent of the usual hyperscalers (AWS/GCP). Tasks As a Senior DevOps Engineer, you won't just manage namespaces or isolated applications; you will have Full Ownership and end-to-end responsibility for the platform operational stability. Your main tasks will include: Platform Operations & Ownership: Actively help shape, deploy, and maintain our cloud Big Data platform infrastructure, taking full responsibility for the operation of our technical data processes. L2/L3 Application Support: Serve as the first point of contact for internal data engineering teams. You will troubleshoot process failures, investigate why a data pipeline failed, and optimize
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