Mid-Level Azure DevOps Engineer

Cyberlocke, LLC•McKinney, TX

3d•$90,000 - $120,000

About The Position

We are seeking a Mid-Level Azure DevOps Engineer to support Microsoft Fabric deployments, Azure-based data platform implementations, and enterprise data modernization initiatives. This role is ideal for someone who has hands-on experience building and supporting cloud environments, deployment pipelines, automation frameworks, and infrastructure for modern data solutions, while also being comfortable presenting technical updates and recommendations to customers. The ideal candidate will help enable reliable, secure, and repeatable deployments for solutions involving Microsoft Fabric, Azure data services, CI/CD pipelines, Infrastructure as Code, and operational automation. This person must also be able to communicate effectively with customer stakeholders, participate in technical workshops, and present project progress, architecture decisions, and deployment plans in a clear and professional way.

Requirements

3–5 years of experience in Azure DevOps, cloud engineering, DevOps engineering, or infrastructure automation roles.
Hands-on experience with Microsoft Azure and Azure resource deployment.
Experience building and maintaining CI/CD pipelines using Azure DevOps.
Experience supporting data platform, analytics, or modernization projects in Azure.
Familiarity with Microsoft Fabric, Azure Data Factory, Azure Synapse, Power BI, or related Microsoft data services.
Experience with Infrastructure as Code using Terraform, Bicep, ARM, or similar tools.
Strong scripting and automation skills using PowerShell, Bash, or Python.
Working knowledge of Azure identity, networking, security, and access control concepts.
Experience with Git repositories, source control workflows, and release management practices.
Ability to troubleshoot technical issues across deployment, infrastructure, and cloud platform layers.
Strong written and verbal communication skills.
Ability to confidently speak with customers and present technical information clearly.
Strong customer presence and professional communication style. This is a customer facing position and you must be able to articulate clearly what you are doing and what you have done for the customers.
Able to explain technical concepts in a business-friendly and organized way.
Comfortable presenting in meetings with customer IT teams, leadership, and project stakeholders.
Detail-oriented and disciplined in documentation, deployment quality, and change control.
Calm and confident when troubleshooting or discussing risks and dependencies.
Collaborative and able to work effectively across engineering, architecture, project management, and customer teams.
Strong organizational and follow-through skills.

Nice To Haves

Experience supporting Microsoft Fabric workspace deployment models and analytics platform promotion across environments.
Familiarity with deployment patterns for Lakehouse, Warehouse, Data Factory pipelines, notebooks, semantic models, and Power BI artifacts.
Experience with modern data architecture concepts such as data lakes, medallion architecture, ETL/ELT, data governance, and analytics pipelines.
Experience in consulting, managed services, or professional services delivery environments.
Familiarity with Azure Monitor, Log Analytics, Application Insights, and operational monitoring practices.
Understanding of security and compliance controls for enterprise data environments.
Experience supporting hybrid environments with on-premises and Azure integration.
Microsoft certifications such as: Microsoft Certified: Azure Administrator Associate, Microsoft Certified: DevOps Engineer Expert, Microsoft Certified: Azure Data Engineer Associate, Microsoft Fabric Analytics Engineer Associate or similar Fabric-related certification.

Responsibilities

Design, build, and maintain Azure DevOps pipelines for Microsoft Fabric, Azure data platforms, and data modernization solutions.
Support deployment automation for data solutions involving Microsoft Fabric, Azure Data Factory, Azure Synapse, Azure Storage, Power BI, and related Azure services.
Implement and maintain CI/CD processes for analytics, integration, reporting, and cloud infrastructure components.
Develop and manage Infrastructure as Code using tools such as Terraform, Bicep, or ARM templates.
Automate environment provisioning, configuration, release management, and operational tasks across development, test, and production environments.
Support source control, branching strategies, release governance, and deployment standards for data engineering and platform teams.
Work with architects, data engineers, analysts, and project teams to ensure successful deployments and environment readiness.
Configure and support monitoring, logging, alerting, and operational visibility across Azure and Fabric environments.
Troubleshoot pipeline issues, release failures, permissions problems, workspace deployment issues, and environment inconsistencies.
Support security, governance, backup, disaster recovery, and compliance requirements for Azure-hosted data environments.
Assist with cost management, environment optimization, and operational improvements across cloud-based data platforms.
Support the deployment and operationalization of modern data platforms for migration and modernization projects.
Help establish repeatable deployment methods for data ingestion, transformation, reporting, and analytics workloads.
Work on projects involving movement of data from on-premises systems to Azure and Microsoft Fabric.
Assist with deployment planning for medallion/layered data architectures, analytics workspaces, semantic models, and reporting environments.
Collaborate with delivery teams to support platform readiness for data governance, quality controls, and production support.
Contribute to documentation, runbooks, deployment guides, and technical standards for modernization initiatives.
Present project updates, technical designs, deployment approaches, risks, timelines, and recommendations to customers.
Participate in customer meetings, workshops, architecture reviews, status calls, and solution discussions.
Translate technical DevOps and cloud deployment concepts into clear language for technical and non-technical audiences.
Explain deployment processes, environment readiness, release planning, and operational considerations to customer stakeholders.
Create customer-ready documentation, implementation summaries, diagrams, and handoff materials.
Represent the engineering team professionally in front of customers and help build trust through clarity, responsiveness, and technical confidence.