Cloud Engineer - Analytica

Analytica is seeking a Mid-Level Cloud Engineer (Azure) to design, deploy, and maintain secure, scalable cloud infrastructure supporting federal data, analytics, and AI modernization initiatives. This role is hands-on and delivery-focused, working within established Azure architectures to implement cloud infrastructure, automate deployments, manage environments, and support the reliability and security of mission-critical applications and data platforms. The Cloud Engineer will work closely with data engineers, software engineers, architects, cybersecurity professionals, and government stakeholders to provision and operate Azure resources that support data pipelines, analytics platforms, applications, and AI/ML workloads. The ideal candidate is comfortable working in a regulated environment and has strong experience with Azure infrastructure, Infrastructure as Code, CI/CD, networking, security, and cloud operations.

Analytica has been recognized by Inc. Magazine as one of the fastest-growing 250 businesses in the US for 3 years. We work with U.S. government clients in health, civilian, and national security missions to build better technology products that impact our day-to-day lives. The company offers competitive compensation with opportunities for bonuses, employer-paid health care, training and development funds, and 401k match.

Key Responsibilities

• Design, deploy, configure, and maintain Azure cloud infrastructure supporting data engineering, analytics, application, and AI/ML workloads.

• Provision and manage Azure resources including Azure Virtual Networks, subnets, NSGs, storage accounts, Azure Key Vault, Azure SQL, Azure Kubernetes Service (AKS), Azure Monitor, and Azure Compute services.

• Build and maintain CI/CD pipelines using Azure DevOps and/or GitHub Actions to automate infrastructure and application deployments.

• Configure and manage Azure networking, including VNets, private endpoints, DNS, routing, firewalls, load balancing, and connectivity between cloud resources and external environments.

• Implement cloud security controls including RBAC, managed identities, secrets management, encryption, network segmentation, and least-privilege access.

• Support the secure integration of Azure infrastructure with data platforms such as Azure Databricks, Azure Data Factory, ADLS Gen2, Synapse Analytics, and Azure SQL.

• Partner with Data Engineers to ensure the underlying cloud infrastructure supports reliable, scalable, and performant data pipelines and analytics workloads.

• Support Databricks infrastructure and workspace integrations, including networking, identity, access controls, compute configuration, and connectivity to Azure resources.

• Configure monitoring, logging, alerting, and operational dashboards using Azure Monitor, Log Analytics, Application Insights, and related Azure services.

• Troubleshoot infrastructure, networking, deployment, performance, and availability issues across development, test, and production environments.

• Automate routine infrastructure and operational processes using PowerShell, Azure CLI, Python, or similar scripting tools.

• Implement cloud cost-management and optimization practices, including resource monitoring, right-sizing, tagging, and appropriate use of compute and storage.

• Support disaster recovery, backup, high availability, and business continuity requirements for cloud-hosted workloads.

• Maintain technical documentation for cloud environments, infrastructure configurations, deployment processes, and operational procedures.

• Contribute to cloud architecture and engineering standards and help identify opportunities to improve scalability, reliability, security, and automation.

• Work within Agile teams and participate in sprint planning, technical discussions, code reviews, demonstrations, and troubleshooting activities.

• Support compliance and security requirements associated with federal cloud environments and applicable agency policies and standards.

Required Qualifications

• U.S. citizenship with the ability to obtain a U.S. Federal security clearance.

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical field, or equivalent professional experience.

• 3+ years of experience in cloud engineering, DevOps, infrastructure engineering, or a related field.

• 3+ years of hands-on experience with Microsoft Azure.

• Experience deploying and managing Azure infrastructure, networking, security, and compute resources.

• Experience with Infrastructure as Code, using Terraform, Bicep, ARM templates, or similar technologies.

• Experience developing and maintaining CI/CD pipelines using Azure DevOps, GitHub Actions, Jenkins, or similar tools.

• Proficiency with Azure CLI and/or PowerShell for cloud administration and automation.

• Experience with Azure identity and security concepts including Microsoft Entra ID, RBAC, managed identities, Key Vault, private endpoints, and network security controls.

• Experience troubleshooting cloud infrastructure, deployments, networking, and application/platform issues.

• Experience working with Git-based source control and collaborative software development practices.

• Strong understanding of cloud networking concepts including VNets, subnets, routing, DNS, firewalls, load balancing, and private connectivity.

Preferred Qualifications

• Experience supporting Azure Databricks, Azure Data Factory, ADLS Gen2, Synapse Analytics, or Azure SQL environments.

• Experience supporting federal, government, or other highly regulated environments.

• Experience with Azure Policy, Microsoft Defender for Cloud, Azure Monitor, Log Analytics, and Microsoft Purview.

• Experience with containerization technologies such as Docker and Kubernetes/AKS.

• Experience with Python or other scripting languages for automation.

• Experience implementing cloud security and compliance controls aligned with FedRAMP, NIST, or other federal security frameworks.

• Experience with CI/CD and DevSecOps practices, including automated security and compliance checks.

• Experience supporting machine learning or AI workloads in Azure, including Azure Machine Learning or MLflow.

• Experience with cloud cost management and FinOps practices.

• Azure certifications such as AZ-104 (Azure Administrator Associate), AZ-305 (Azure Solutions Architect Expert), or AZ-400 (DevOps Engineer Expert).

• Experience working in Agile/Scrum development environments.