via Lever.co
$150K - 205K a year
You would design and maintain secure, scalable cloud infrastructure, automate it with infrastructure-as-code, and support hybrid multi-cloud environments under healthcare compliance requirements.
The role requires extensive Azure enterprise platform and hybrid-cloud experience, deep Terraform, CI/CD, Kubernetes, and identity-management proficiency, and experience in regulated healthcare.
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead Cloud Engineer (Azure) based in the United States. We are seeking an experienced Lead Cloud Engineer to design, build, and maintain secure, scalable cloud infrastructure within an enterprise data environment. In this role, you will lead infrastructure automation, platform provisioning, and hybrid multi-cloud integration across Microsoft Azure and Google Cloud Platform. You will play a key role in implementing high-availability architectures, secure networking, identity management, and enterprise-grade data services. Working with modern technologies such as Terraform, Azure Kubernetes Service (AKS), Azure DevOps, and Microsoft Entra ID, you will help establish reliable and repeatable cloud engineering practices. You will also ensure that infrastructure meets stringent healthcare security, privacy, and regulatory requirements, including HIPAA and Protected Health Information (PHI) safeguards. This remote opportunity is ideal for a technically strong cloud engineer who enjoys solving complex infrastructure challenges and building secure, automation-driven platforms. \n Accountabilities Infrastructure as Code and Automation: Design, develop, and maintain reusable Terraform modules and deployment pipelines to provision and manage Azure enterprise data infrastructure, including networking, security controls, resource groups, and service integrations. Cloud Architecture and Environment Management: Implement and maintain a three-plane architecture comprising the Control Plane, Data Plane, and Target Stores across designated Azure subscriptions and resource groups, supporting both high-assurance staging and production environments and lower-assurance development and testing environments. Hybrid Multi-Cloud Connectivity: Configure secure private networking between Azure and Google Cloud data services, enabling connectivity to BigQuery, Cloud Storage, FHIR Store, and DICOM Store through private endpoints without exposing sensitive workloads to the public internet. Azure Platform Services: Deploy, configure, and maintain Azure Kubernetes Service (AKS), Azure Database for PostgreSQL Flexible Server with pgvector, Blob Storage, Azure Key Vault, Azure Container Registry (ACR), and Azure Artifacts. Containerization and Workload Orchestration: Support the deployment and operation of containerized workloads, including Apache Airflow, Milvus, Neo4j operators, and custom applications, with appropriate Kubernetes configurations and GPU-enabled node pools where required. Identity and Access Management: Implement Microsoft Entra ID authentication and role-based access control (RBAC), enforce least-privilege permissions, integrate SailPoint-governed groups, manage personal service accounts, and support just-in-time (JIT) privileged access. Monitoring and Observability: Configure centralized logging, monitoring, and telemetry using Azure Monitor, ensuring that operational logs and audit records are designed to exclude Protected Health Information (PHI). Security and Regulatory Compliance: Apply encryption, access controls, secure connectivity, data residency requirements, and secure software development lifecycle practices to protect sensitive healthcare data and maintain compliance. CI/CD and Delivery Engineering: Build and maintain automated infrastructure deployment pipelines using Azure DevOps and GitHub Enterprise, incorporating testing, validation, security checks, and repeatable release processes. Platform Reliability and Continuous Improvement: Identify and resolve infrastructure, networking, security, and deployment issues while improving cloud performance, reliability, scalability, and operational efficiency. Cross-Functional Collaboration: Partner with data engineers, platform teams, security specialists, and other technical stakeholders to establish cloud engineering standards, resolve complex technical challenges, and deliver dependable enterprise data capabilities. Requirements Cloud Engineering Expertise: Extensive hands-on experience with Microsoft Azure enterprise data platforms, including infrastructure design, provisioning, networking, security, and operational support. Hybrid Multi-Cloud Architecture: Demonstrated experience designing and implementing secure hybrid or multi-cloud environments, particularly integrations between Azure, Google Cloud Platform, and Microsoft Fabric. Infrastructure as Code: Deep proficiency in Terraform, including reusable module development, infrastructure lifecycle management, and enterprise-scale deployment practices. Experience with Spacelift or Terraform Enterprise is highly desirable. CI/CD and Automation: Strong experience building and managing automated deployment pipelines using Azure DevOps and GitHub Enterprise, with an emphasis on repeatability, security, and operational consistency. Kubernetes and Containerization: Proven experience deploying and operating workloads on Azure Kubernetes Service (AKS), including Apache Airflow, Milvus, Neo4j operators, and custom applications. Experience configuring GPU-enabled node pools is also important. Azure Platform Services: Practical knowledge of Azure networking, storage, Key Vault, Azure Database for PostgreSQL Flexible Server, Azure Container Registry, Azure Artifacts, and enterprise resource management. Identity and Access Management: Strong understanding of Microsoft Entra ID, RBAC, least-privilege access, privileged identity management, service accounts, and enterprise identity governance solutions such as SailPoint. Healthcare Security and Compliance: Working knowledge of HIPAA requirements, PHI protection, data residency restrictions, encryption standards, and secure SDLC practices. Familiarity with TLS 1.2 or higher, encryption at rest, and key management is essential. Observability and Operational Security: Experience implementing centralized monitoring, logging, telemetry, and audit controls while ensuring sensitive information is excluded from logs and diagnostic outputs. Technical Problem-Solving: Strong analytical and troubleshooting skills, with the ability to resolve complex cloud infrastructure, connectivity, container orchestration, and security issues. Collaboration and Communication: Ability to work effectively with multidisciplinary technical teams, communicate complex concepts clearly, and contribute to architectural decisions and engineering standards. Continuous Improvement: A proactive approach to automation, infrastructure optimization, security enhancement, and adopting cloud engineering best practices. Benefits Competitive annual salary: $150,000–$205,000, depending on experience, expertise, geographic location, and final role level. Comprehensive health insurance: Health coverage designed to support employee well-being. Retirement savings: A 401(k) plan with employer matching. Paid time off: Vacation and paid leave to support work-life balance. Paid holidays: Company-provided paid holidays. Sick leave: Paid leave for illness and health-related needs. Parental leave: Support for employees welcoming a new child. Bereavement leave: Time off to manage personal and family loss. Employee referral bonuses: Opportunities to earn bonuses for eligible referrals. Remote work flexibility: A remote position based in the United States. Advanced technology exposure: Opportunities to work with Azure, Google Cloud, Kubernetes, Terraform, and modern enterprise data platforms. Professional development: The opportunity to strengthen expertise in cloud architecture, infrastructure automation, multi-cloud integration, and healthcare data security. Meaningful technical impact: The chance to build secure, scalable cloud foundations that support sensitive data workloads and enterprise-level innovation. \n How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1
This job posting was last updated on 10/20/2026