Director, Cloud Transformation

Quanta Services Management Partnership•Houston, TX

About The Position

The Director of Cloud Transformation is a senior technical leadership role within QCOIT, responsible for accelerating Quanta’s migration from on-premise infrastructure to a cloud-native operating model. This role is central to Quanta’s IT transformation strategy: transitioning routine infrastructure operations to managed service providers (MSPs) while building modern, scalable, and cost-efficient cloud capabilities that unlock the full potential of AI, data analytics, and custom application development across the enterprise. This individual will lead application modernization efforts using AI-assisted development tools (e.g., Claude Code), architect cloud-native solutions on AWS and Azure, and build the observability and DevOps practices required to run enterprise applications with minimal administrative overhead. The role requires a unique blend of deep technical expertise, strategic program leadership, and the ability to operate effectively in a complex, multi-operating-company

Requirements

10+ years of progressive experience in cloud engineering, cloud architecture, or infrastructure modernization, with at least 5 years in a leadership role.
Deep hands-on expertise with AWS services, particularly serverless (Lambda, API Gateway, Step Functions, DynamoDB, S3, EventBridge) and container platforms (ECS, EKS, Fargate).
Strong working knowledge of Azure cloud services and familiarity with multi-cloud operating models.
Proven experience leading large-scale cloud migration programs (500+ servers or 100+ applications) in complex, multi-business-unit environments.
Expert-level proficiency in DevOps toolchains: CI/CD (GitHub Actions, Azure DevOps, Jenkins), IaC (Terraform, CloudFormation/CDK), containerization (Docker, Kubernetes), and GitOps practices.
Deep understanding of observability platforms (Dynatrace, Datadog, CloudWatch, Grafana) and the ability to design monitoring strategies that balance enterprise rigor with operational simplicity.
Experience with AI-assisted development tools and the ability to integrate them into modernization workflows to accelerate delivery.
Strong financial acumen—ability to build business cases, model cloud economics, and communicate ROI to CFO-level audiences.
Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field. Master’s degree preferred.

Nice To Haves

AWS Solutions Architect Professional or AWS DevOps Engineer Professional certification.
Experience in construction, engineering, energy, or infrastructure industries.
Familiarity with ERP platforms (JD Edwards, SAP, Oracle) and their cloud migration considerations.
Experience managing MSP/outsourced provider relationships in a hybrid operating model.
Track record of building cloud engineering teams from the ground up and establishing centers of excellence.
Experience with Databricks, data platform architecture, or enabling AI/ML workloads on cloud infrastructure.

Responsibilities

Lead the modernization of legacy applications across the Quanta enterprise, transforming on-premise workloads into cloud-native architectures that deliver orders-of-magnitude cost improvements and operational simplification.
Pioneer the use of AI-assisted development tools—specifically Claude Code and similar platforms—to dramatically reduce modernization timelines and costs, making previously uneconomical technical debt remediation now viable.
Develop and maintain a modernization playbook with repeatable patterns for common application archetypes found across Quanta’s 85+ operating companies, including ERP integrations, field operations tools, and business intelligence platforms.
Evaluate applications in the enterprise portfolio (1,300+ application instances) to identify and prioritize modernization candidates based on business value, technical debt, and cloud-readiness.
Serve as the enterprise’s foremost authority on cloud-native architecture, with deep expertise in serverless computing (AWS Lambda, API Gateway, Step Functions, DynamoDB), container orchestration (ECS/EKS), and event-driven design patterns.
Design reference architectures that bring the full benefits of cloud computing—including auto-scaling, pay-per-use economics, built-in high availability, and zero-server management—to Quanta’s application portfolio.
Architect solutions across Quanta’s multi-cloud environment: AWS (primary for new workloads and AI/data platforms), Azure (enterprise infrastructure and M365 ecosystem), and OCI (Oracle Exadata for critical databases).
Establish cloud design standards, patterns, and guardrails that enable operating companies to build and deploy applications within a governed framework while maintaining the agility they need.
Build and operationalize a comprehensive observability strategy using enterprise-grade monitoring platforms such as Dynatrace, Datadog, and/or AWS CloudWatch to ensure cloud-native applications meet enterprise requirements for availability, performance, security, and compliance.
Design monitoring architectures that minimize administrative overhead—leveraging automated alerting, self-healing capabilities, and intelligent anomaly detection to reduce the need for manual intervention.
Define and enforce service-level objectives (SLOs) and operational readiness standards (the “ilities”: reliability, scalability, observability, security, maintainability, recoverability) for all cloud-deployed applications.
Create operational dashboards that provide real-time visibility into application health, cost, and performance for both IT leadership and operating company stakeholders.
Architect and lead Quanta’s large-scale cloud migration program, coordinating across multiple operating companies, MSP partners (Neudesic for Azure, LTI Mindtree for OCI, Trek10 for AWS), and internal IT teams.
Develop migration wave plans that account for application dependencies, operating company readiness, business continuity requirements, and the planned NTT data center exit.
Create and manage the technical migration framework including discovery, assessment, migration execution, validation, and optimization phases for each workload.
Partner with the VP of IT, Directors of Solution Architecture, and Enterprise Architecture team to align migration priorities with the broader 5-year IT strategy and OpCo value delivery objectives.
Build business cases for migration initiatives that translate technical benefits into the financial language executives expect: ROIC, payback periods, cost avoidance, and operational risk reduction.
Develop and deliver cloud enablement programs for Quanta’s Software Development, Data & AI, and Cloud Enablement teams, raising the cloud maturity of the entire IT organization.
Create hands-on training curricula covering serverless development, Infrastructure-as-Code (Terraform/CloudFormation), CI/CD pipelines, containerization, and cloud-native security practices.
Establish a community of practice around cloud engineering, facilitating knowledge sharing, architectural reviews, and collaborative problem-solving across teams.
Coach and mentor the existing Cloud Enablement Team (~10 people), elevating their capabilities from Azure-centric operations to multi-cloud architecture and cloud-native development.
Partner with MSP providers to ensure knowledge transfer flows both directions—leveraging MSP expertise to accelerate internal team development while ensuring Quanta retains critical architectural knowledge.
Establish and mature DevOps practices across QCOIT, including CI/CD pipeline design, Infrastructure-as-Code (IaC), GitOps workflows, automated testing, and release management.
Design and implement platform engineering capabilities that enable development teams to self-service infrastructure provisioning, environment management, and deployment within governed guardrails.
Build automated compliance and security scanning into deployment pipelines, ensuring cloud workloads meet enterprise security standards without creating manual bottlenecks.
Implement cost management automation including right-sizing recommendations, idle resource cleanup, reserved instance optimization, and real-time spend alerting.
Define and track DevOps maturity metrics (deployment frequency, lead time, change failure rate, mean time to recovery) to drive continuous improvement.