IT Manager – Platform Engineering, Data Science

Jobtailor

Newport News (VA)

On-site

USD 180,000 - 240,000

Full time

14 days+

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Job summary

Ferguson is seeking an experienced platform engineering leader to drive the cloud and data science roadmap in a hybrid-cloud environment. You will lead a cross-functional team of platform engineers, architects, and specialists to deliver scalable, secure platform services on Google Cloud Platform with Azure support for hybrid workloads.

The role emphasizes DevSecOps, CI/CD, and MLOps, enabling ML workflows and dashboards for telemetry and data analytics.

Qualifications

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 business domains.
Direct experience leading engineering or technical talent, including performance management for direct reports; offshore/onsite consultants preferred.
Java and/or Python programming with Software Architecture and Engineering expertise.
Experience in secure software delivery (DevSecOps) and CI/CD and pipeline development.
Hands-on experience operating platform services on Google Cloud Platform (GCP) with hybrid-cloud knowledge (Azure helpful).
Experience enabling data science and ML workflows using cloud-native tooling (Vertex AI, BigQuery, etc.).
Experience creating operational dashboards, telemetry configurations and alerting templates.

Responsibilities

Lead, coach, and develop a high-performing team of platform engineers, architects, and specialists.
Define and execute the platform engineering, cloud, and data science roadmap.
Design, build, and optimize scalable, secure platform capabilities across GCP and hybrid-cloud environments.
Partner with AI Engineering, Data Science, Product, and Architecture teams to enable AI/ML deployment and operations.
Drive DevSecOps, CI/CD, automation, and platform reliability standards.
Own and enhance MLOps and data science platform capabilities for model development and deployment.
Establish standards, API strategies, and reusable platform services to accelerate delivery.
Lead platform modernization initiatives including cloud adoption and automation.
Manage delivery, budgets, vendor relationships, and team capacity.
Supervise platform performance, security, availability, and scalability; mitigate risks.
Build partnerships with business and technology leaders to align investments.
Stay ahead of emerging cloud, AI, data, and engineering tech to drive innovation.

Skills

Platform Leadership

Cloud Architecture

Machine Learning

DevSecOps

MLOps

Team Leadership

Performance Management

Collaboration

Proactive Initiative

Education

Bachelor’s degree in information technology, computer science or related field

Tools

Java

Python

Vertex AI

BigQuery

AppDynamics

DataDog

Telemetry

GCP

Job description

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

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.

Core Competencies

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.

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