Data Platform Administrator

Description

Position Summary: Administer a critical data platform with emphasis on Cloudera and hybrid integrations, collaborating with teams to ensure data reliability for business use cases, analytics, and ML/AI. Key Highlights: 1. Critical Data Platform Administration (Cloudera, Hybrid) 2. Collaboration in Evolving Data and Analytics Ecosystem 3. Mindset of Continuous Improvement and Automation Administration of a critical data platform, with particular focus on Cloudera environments and hybrid cloud integrations. Responsibilities include ensuring system availability, performance, security, and scalability, as well as performing monitoring and security hardening tasks. Incident management, change implementation, updates, and problem resolution are conducted to improve service quality. Automation of operational and deployment tasks is essential to enhance overall reliability and efficiency. Collaborate with data engineering, analytics, and architecture teams to ensure connectivity and interoperability with both on-premises and cloud-based corporate environments, such as Oracle DWH, Denodo, Google Cloud Platform, and Microsoft Azure. Understand how the platform enables business use cases, advanced analytics, machine learning, and artificial intelligence—where data reliability is a critical factor. The work environment values a service-oriented mindset, treating the platform as an internal product. We seek methodical individuals focused on continuous improvement, automation, and quality, with a collaborative and proactive attitude. This position is part of a strategic initiative to evolve the data and analytics ecosystem in Elorrio. Required education includes degrees in Computer Engineering, Business Analytics, Business Administration and Management, or Data Governance. Solid experience operating data platforms and complex analytical environments is required. Experience in big data and hybrid on\-premise/cloud environments is preferred, with specific expertise in Cloudera, distributed processing, and technologies such as PySpark, SQL, Apache Iceberg, dbt, Google Cloud Platform, or Azure. Knowledge of enterprise environments such as Oracle DWH and Denodo is also required. Competencies in security, performance, monitoring, automation, and access control are essential.