Ardent is hiring a
Cloud Solutions Engineer

Summary

Join Ardent as a Cloud Solutions Engineer and contribute to designing, developing, and implementing cloud-based solutions. As a member of our team, you will collaborate with cross-functional teams, implement Azure-based solutions, develop PowerBI dashboards, and leverage ESRI tools. We offer competitive benefits, professional development opportunities, and an exceptional culture that values flexibility, innovation, collaboration, and career growth.

Requirements

• Bachelor's degree in Computer Science, Engineering, or related field (Master's preferred)
• 3-5 years of experience in cloud engineering, with 3 years specifically in Azure-based solutions
• Proficient in Azure cloud services with hands-on experience in designing and deploying solutions
• Strong knowledge of PowerBI for data visualization and reporting
• Expertise in ESRI tools required (Desktop, Online, Portal) for geospatial data management and analysis
• Familiarity with DevSecOps principles and their application in cloud environments
• Proficiency in Python scripting for automation and integration purposes
• Experience with ETL processes and their implementation
• Strong command of SQL for data querying, manipulation, and optimization
• Familiarity with Databricks and Spark for big data processing and analytics
• Experience with Collabera or similar collaboration platforms

Responsibilities

• Collaborate closely with cross-functional teams to understand business requirements and design effective cloud solutions
• Implement and manage Azure-based solutions utilizing various Azure services and resources
• Develop and maintain PowerBI dashboards and reports to provide actionable insights
• Leverage ESRI tools (Desktop, Online, Portal) to integrate geospatial capabilities into cloud solutions
• Apply DevSecOps best practices to ensure security, compliance, and automation within the cloud environment
• Create and maintain Python scripts for automation, orchestration, and integration tasks
• Design and implement ETL processes for efficient data extraction, transformation, and loading
• Optimize SQL queries, databases, and data pipelines for performance and reliability