Senior DevOps Engineer; AI & Cloud Platform-Locals

Duration

12+ Months Contract (Extension Possible)

Virtual/In-Person Interview

• Design, implement, and maintain enterprise-grade Dev Ops processes and CI/CD pipelines.
• Build and manage scalable, secure, and highly available cloud infrastructure on Microsoft Azure.
• Administer and optimize Snowflake environments, including performance tuning, warehouse management, and access controls.
• Develop automation solutions using Python for deployment, monitoring, and operational efficiency.
• Implement and support containerized workloads using Kubernetes and Azure Kubernetes Service (AKS).
• Design, develop, and maintain cloud-based data pipelines and ETL processes.
• Integrate AI/ML platforms and services into enterprise data ecosystems.
• Configure and manage centralized logging, monitoring, alerting, and observability solutions.
• Implement security best practices, governance policies, and role-based access controls (RBAC).
• Collaborate with architects, developers, data engineers, and business stakeholders to deliver cloud and data solutions.
• Analyze business requirements and recommend technical solutions through cost-benefit analysis and feasibility studies.
• Create technical documentation, operational procedures, and implementation guides.
• Monitor system performance and proactively identify optimization opportunities.

• 8+ years of experience with Dev Ops practices and tools, including Azure Dev Ops, Git, and CI/CD pipelines.
• 8+ years of hands‑on experience with Microsoft Azure Cloud Platform.
• 8+ years of Snowflake administration experience, including:
  • RBAC and security management
  • Least privilege access controls
  • Performance tuning
  • Warehouse optimization and management
• 8+ years of Python scripting experience for automation and data engineering.
• 8+ years of experience with containerization and orchestration technologies (AKS preferred).
• Strong experience with data pipelines, ETL processes, and cloud data integration.
• Experience integrating AI/ML technologies into cloud platforms.
• Expertise with Azure Monitor, Log Analytics, centralized logging, dashboarding, and alerting.
• Strong understanding of monitoring, observability, and operational excellence.
• Experience gathering requirements, evaluating alternatives, and recommending technical solutions.

• Experience implementing AI-enabled data platforms, including Snowflake Cortex and ML pipelines.
• Experience with Infrastructure as Code (IaC) tools such as Terraform, ARM, or Bicep.
• Knowledge of data security, governance, compliance, and regulatory frameworks.
• Experience supporting public sector or large enterprise environments.
• Exposure to Snowflake AI and Cortex capabilities.
• Strong analytical, troubleshooting, and problem‑solving skills.
• Ability to manage multiple priorities in fast‑paced environments.
• Strong documentation and communication skills.
• Detail‑oriented with a commitment to engineering best practices.