Senior DevOps Engineer (Systems Analyst III) - 26-06932

Job summary

Seeking an experienced Senior DevOps Engineer to support enterprise cloud, data, and AI initiatives. This role involves designing, implementing, and maintaining scalable, secure, and automated cloud environments, CI/CD pipelines, data platforms, and AI-enabled solutions. The ideal candidate will possess deep expertise in Azure cloud technologies, Snowflake administration, DevOps automation, container orchestration, Python scripting, and modern data engineering practices.

Qualifications

• 8+ years of experience with Azure DevOps.
• 8+ years of experience with Git.
• 8+ years of experience with CI/CD Pipeline Development.
• 8+ years of hands-on Microsoft Azure cloud experience.
• 8+ years of Snowflake administration experience including RBAC and security administration, access management, warehouse management, and performance tuning.
• 8+ years of Python scripting and automation experience.
• 8+ years of containerization and orchestration experience (AKS preferred).
• 8+ years working with data pipelines, ETL processes, and cloud data integration.
• 8+ years supporting AI/ML platform integration.
• 8+ years with Azure Monitor, Log Analytics, centralized logging, alerting, dashboarding, and security monitoring.
• Strong experience with observability, monitoring, and operational support tools.
• Experience implementing Infrastructure as Code (IaC).
• Knowledge of cloud governance and enterprise architecture principles.
• Experience with AI-enabled data platforms.
• Experience with Snowflake Cortex, Snowflake AI features, and Machine Learning pipelines.
• Knowledge of data security frameworks, compliance standards, and governance best practices.
• Public sector experience preferred.
• Large enterprise environment experience preferred.

Responsibilities

• Design, implement, and maintain enterprise DevOps practices and processes.
• Build and manage CI/CD pipelines supporting cloud and data platforms.
• Automate deployment, monitoring, testing, and operational workflows.
• Support application and infrastructure lifecycle management.
• Architect and administer Microsoft Azure environments.
• Manage cloud infrastructure, services, networking, and security controls.
• Optimize cloud performance, scalability, reliability, and cost efficiency.
• Implement Azure governance and operational best practices.
• Administer enterprise Snowflake environments.
• Manage role-based access control (RBAC) and security policies.
• Implement least-privilege access models.
• Perform performance tuning and warehouse optimization.
• Monitor platform health, usage, and resource consumption.
• Design and support cloud-based data pipelines and ETL processes.
• Enable secure movement and integration of enterprise data assets.
• Support analytics, reporting, and AI initiatives through optimized data architectures.
• Collaborate with data engineering teams to improve data reliability and performance.
• Support integration of AI and machine learning platforms within cloud environments.
• Assist with deployment and operationalization of AI-enabled data solutions.
• Contribute to AI pipeline automation and monitoring.

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Relocation