IT Manager – Platform Engineering, Data Science

Ferguson

Manager of Platform Engineering & Data Science at Ferguson driving AI technology and cloud capabilities. Leading a high-performing team to deliver scalable software solutions and innovations.

Posted 7/29/2026full-timeNewport News • Virginia • 🇺🇸 United StatesMid-LevelSenior💰 $7,569 - $13,248 per monthWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in platform engineering, cloud architecture, and machine learning implementation, with a strong focus on driving DevSecOps practices and optimizing platform capabilities on Google Cloud Platform. Proven ability to lead and develop high-performing teams while managing project delivery and aligning technology investments with business priorities.

Highest-signal resume keywords

Platform EngineeringMachine Learning ImplementationGoogle Cloud Platform (GCP)DevSecOpsSoftware Architecture

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Applicant Tracking System Keywords

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Hard Skills

JavaPythonSoftware ArchitectureCI/CDMLOpsData AnalyticsCloud-Native ToolingSoftware Design PatternsInfrastructure AutomationAPI Strategies

Soft Skills

Team LeadershipCoachingPerformance ManagementCollaborationProactive Initiative

Tools & Technologies

Vertex AIBigQueryAppDynamicsDataDogTelemetry Configurations

Industry Keywords

Cloud AdoptionPlatform ModernizationOperational DashboardsHybrid-Cloud EnvironmentsSoftware Delivery Standards

Tech Stack

Tools & technologies

AzureBigQueryCloudGoogle Cloud PlatformJavaPython

About the role

Key responsibilities & impact

Lead, coach, and develop a high-performing team of platform engineers, architects, and technical specialists.
Define and execute the platform engineering, cloud, and data science roadmap in support of Ferguson's AI and technology strategy.
Design, build, and optimize scalable, secure, and reliable platform capabilities across Google Cloud Platform (GCP) and hybrid-cloud environments.
Partner with AI Engineering, Data Science, Product, and Architecture teams to enable the development, deployment, and operation of AI and machine learning solutions.
Drive DevSecOps, CI/CD, infrastructure automation, and platform reliability standards to improve delivery speed, quality, and operational efficiency.
Own and enhance MLOps and data science platform capabilities, supporting model development, training, deployment, and monitoring at scale.
Establish engineering standards, architecture patterns, API strategies, and reusable platform services that accelerate software delivery.
Lead platform modernization initiatives, including cloud adoption, developer experience improvements, automation, and legacy technology retirement.
Manage project delivery, budgets, vendor relationships, and team capacity to ensure successful execution of critical initiatives.
Supervise platform performance, security, availability, and scalability while proactively identifying and mitigating risks.
Build strong partnerships with business and technology leaders to align platform investments with organizational priorities.
Stay ahead of emerging cloud, AI, data, and engineering technologies to drive innovation and continuous improvement.

Requirements

What you’ll need

Bachelor’s degree in information technology, computer science or related field preferred, or equivalent experience.
At least 5 years of hands-on experience in platform engineering.
Experience in machine learning implementation and data analytics enablement is required.
Broad knowledge of how platform capabilities support integration and innovation across different business domains.
Prior experience directly leading engineering or technical talent, including performance management and career development for direct reports; experience with offshore/onsite consultants preferred.
Direct experience in software programming with Java and/or Python, along with Software Architecture and Engineering expertise.
Experience in secure software delivery (DevSecOps) and continuous integration/continuous deployment (CI/CD), and pipeline development.
Hands-on experience architecting and operating platform services on Google Cloud Platform (GCP) as the primary hyperscaler, with working knowledge of Azure to support hybrid-cloud workloads and legacy system integration.
Experience enabling data science and ML workflows using cloud-native tooling (e.g., Vertex AI, BigQuery, or equivalent feature-store, pipeline-orchestration, and model-serving constructs) strongly preferred.
Experience creating operational dashboards, telemetry configurations and alerting templates for end-to-end flow of data services using APM and Data Logging solutions such as AppDynamics, DataDog etc.
Solid understanding and experience implementing software design patterns and modern standards.
Hands-on software engineer able to work alongside a cross-functional team of software engineers, software architects, data scientists, and software quality engineers as needed.
Proactive initiative to find opportunities to improve the platform and data science tooling rather than waiting for direction.

Benefits

Comp & perks

Health insurance
Dental insurance
Vision insurance
Paid time off
Life insurance
401(k) with company match
Mental health coverage
Gender affirming benefits
Family building benefits
Paid parental leave
Associate discounts
Community involvement opportunities