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Mid-Level Data Engineer
SysMap Solutions. Maintain data environments and processes in Azure and on-premises environments, ensuring continuous and reliable operations .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in Data Engineering with a focus on production support, incident management, and continuous improvement of DataOps and CI/CD pipelines. Proficient in managing data environments in Azure and Databricks while ensuring compliance with security and governance best practices.
Highest-signal resume keywords
Data EngineeringDatabricks SupportMicrosoft AzureIncident ManagementData Integration
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data Pipeline DevelopmentData ModelingData IntegrationProduction SupportTroubleshootingMonitoringProblem ManagementSLA ManagementCI/CD PipelinesData Governance
Soft Skills
CollaborationCommunicationPrioritization
Tools & Technologies
AzureDatabricks
Certifications & Qualifications
Degree in Information TechnologyDegree in Data Engineering
Industry Keywords
DataOpsCloud EnvironmentsObservabilityAnalytics EnvironmentsSecurity Best Practices
Tech Stack
Tools & technologiesAzureCloud
About the role
Key responsibilities & impact- 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
Requirements
What you’ll need- 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