Mid-Level Data Engineer

• Maintain data environments and processes in Azure and on-premises environments, ensuring continuous and reliable operations
• Provide administration and advanced support for Databricks on Azure, including troubleshooting and operational adjustments
• Monitor and oversee pipelines, jobs, integrations, and data routines with a preventive and corrective approach
• Implement fixes and improvements to existing processes, identifying root causes and reducing recurrence
• Lead incident management and resolution, including SLA management, prioritization, communication, and follow-up through stabilization
• Support BI and development teams by ensuring environments are ready for new releases and requirements
• Continuously evolve and improve DataOps and CI/CD pipelines for data, focusing on governance, quality, and reliability
• Collaborate with infrastructure and architecture teams as needed on capacity, access, security, networking, and performance
• Ensure compliance with security, governance, and compliance best practices in the data environment
• Propose and implement improvements to observability, monitoring, and alerting, including metrics, logs, and traceability

• Mid-level experience in Data Engineering with a focus on production support and operations, not only greenfield projects
• Strong experience with Databricks, including troubleshooting and supporting jobs and pipelines
• Experience working in cloud environments, preferably Microsoft Azure
• Experience supporting pipelines, integrations, and data processes in production
• Knowledge of monitoring, incident management, and problem management, including SLA management, prioritization, response, and post-incident activities
• Strong experience in data projects, pipeline development and support, data integration, data modeling, and work in analytics environments
• Degree in Information Technology and/or Data Engineering