Data Scientist I

Job Overview

Do you enjoy building and managing the deployment systems that power enterprise-grade data science and AI applications at scale We're seeking a Cloud Deployment Engineer to join our Platform Engineering Practice and own the deployment pipelines, release processes, and operational stability of our cloud-first analytics platforms on Azure. You'll design deployment methods, implement automation, troubleshoot complex deployment failures, and ensure our solutions reach production reliably, securely, and repeatably.

**Why This Role Is Critical:**This position is foundational to our ability to deliver secure, scalable, and reliable cloud-native solutions to our clients. The engineer in this role becomes the trusted infrastructure partner to our data science, analytics, and AI teams, ensuring systems remain available, secure, and cost-effective while supporting rapid innovation cycles.

The candidate in this role will join a growth path that expands cloud infrastructure expertise:

• Design and implement deployment methods, pipelines, and processes for cloud-first solutions on Azure including App Services, Azure Functions, Container Registry, and storage services
• Build and optimize CI/CD pipelines in enterprise cloud environments using Azure DevOps to automate testing, building, and deploying applications
• Implement Infrastructure as Code (IaC) practices using Terraform, ARM templates, or Bicep for repeatable, version-controlled deployments
• Containerize applications using Docker and manage container deployments in Azure environments
• Troubleshoot and resolve complex failures at all stages from deployment pipelines through to running production systems including reading and diagnosing issues at the code level
• Review infrastructure-as-code and application code for deployment readiness, identifying issues before they reach production
• Establish monitoring, logging, and alerting strategies using Azure Monitor, Application Insights, and Log Analytics to maintain deployment health
• Compose automation scripts to streamline deployment, configuration, health checks, and operational tasks

Experience Needed:

Required:

• 1+ years industry experience with at least 6+ months hands-on Azure cloud platform work
• Demonstrated experience deploying and managing applications on Azure App Services, Azure Functions, or similar PaaS offerings
• Demonstrated experience building and maintaining CI/CD pipelines in enterprise environments (Azure DevOps, GitHub Actions, Jenkins)
• Strong proficiency in Python for deployment automation and scripting
• Hands-on experience with Docker containerization and container deployment in cloud environments
• Infrastructure as Code proficiency with at least one tool (Terraform, ARM templates, or Bicep)
• Experience with application monitoring platforms (Azure Monitor, Application Insights, Log Analytics)
• Strong troubleshooting methodology across the full stack - deployment pipelines, running systems, and application code - with the ability to diagnose and resolve complex multi-component failures

Desirable:

• Networking experience with Virtual Networks, service endpoints, private endpoints, and DNS
• MLOps concepts and deployment patterns
• Azure Data Factory or similar ETL orchestration tools
• Familiarity with compliance frameworks (SOC 2, FedRAMP, HIPAA)

Education:

• BS or Masters degree in Computer Science, Software Engineering, or related technical discipline