Endpoint Intelligence & Automation Engineer

General Motors; Warren (MI); On-site; USD 110,000 - 160,000; Full time

Job summary

General Motors seeks an Endpoint Intelligence & Automation Engineer to lead how we measure and improve health and digital experience of GM end user endpoints. You will own telemetry strategy, create dashboards, and translate data into actionable engineering decisions.

You will partner with endpoint engineering, security, and operations to build scalable data pipelines, automate collection, and drive continuous improvement across Windows, macOS, Linux, and VDI environments.

Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Analytics, or equivalent experience.
• 6+ years in endpoint engineering, endpoint management, or analytics roles.
• Experience gathering telemetry from endpoint ecosystems and operational data sources.
• Ability to create reports, dashboards, and presentations for diverse audiences.
• Strong analytical skills to identify patterns and insights in large datasets.
• Hands-on experience with Windows, macOS, Linux, or VDI in large environments.
• Proficiency in scripting and automation (PowerShell, Python, SQL).
• Ability to translate data into actionable recommendations and executive summaries.

Responsibilities

• Own endpoint telemetry and digital experience insights strategy within End User Engineering.
• Gather, normalize, and analyze telemetry from computers and related platforms.
• Define KPIs for endpoint health, stability, compliance, and UX.
• Build dashboards, reports, and scorecards for engineers and leadership.
• Turn telemetry into recommendations to improve reliability and security.
• Collaborate with engineering to create scalable data pipelines and automation.
• Automate data collection and reporting to reduce manual effort.
• Support root cause analysis by linking telemetry to incidents.
• Measure impact of platform changes with data-driven reporting.
• Establish data quality governance for endpoint telemetry.

Skills

Endpoint telemetry

Data analysis

Dashboards

Communication

Automation

Education

Bachelor’s degree in CS/Eng/Data Analytics

Tools

PowerShell

Python

SQL

Power BI

Tableau

Job description

Job Description

The Endpoint Intelligence & Automation Engineer is responsible for defining how General Motors measures, understands, and improves the health, performance, and digital experience of end user endpoints across the enterprise.

This role owns the strategy and execution for endpoint telemetry, reporting, and experience insights across computers and endpoint management systems.

You will gather and connect data from endpoint platforms, management tooling, support systems, and operational sources to build a clear view of endpoint health, compliance, reliability, and user experience.

You will help establish the guardrails for how endpoint intelligence is collected, interpreted, and communicated — determining what signals matter most, how those signals are correlated, what constitutes a healthy endpoint experience, and how engineering and leadership teams should use that information to make decisions.

This role partners closely with endpoint engineering, platform teams, security, infrastructure, support, and leadership stakeholders to translate endpoint telemetry into actionable reporting, automation, and continuous improvement.

What You’ll Do

• Own the endpoint telemetry, reporting, and digital experience insights strategy as part of the broader End User Engineering mission
• Gather, normalize, and analyze telemetry from computers, endpoint management platforms, support systems, and related operational data sources
• Define and maintain key performance indicators for endpoint health, stability, compliance, performance, and user experience
• Build and maintain dashboards, scorecards, and reports for engineers, operational teams, and leadership audiences, with opportunities to leverage AI-assisted reporting and insight generation
• Translate telemetry signals into clear recommendations that improve endpoint reliability, supportability, security, and end user experience
• Partner with engineering teams to turn endpoint intelligence requirements into scalable data pipelines, automation, and reporting capabilities
• Create automated collection, correlation, and reporting processes that reduce manual effort and improve visibility across the environment, including the use of AI to help surface trends and relationships in data
• Support root cause analysis by connecting telemetry signals to incidents, degradations, misconfigurations, and service disruptions
• Measure the impact of platform changes, OS updates, policy changes, patching, and engineering initiatives using data-driven reporting
• Establish reporting standards, data quality practices, and governance for endpoint intelligence and experience measurement
• Communicate trends, risks, and improvement opportunities clearly to both technical and non-technical stakeholders
• Contribute to roadmap planning by using endpoint data and experience insights to inform priorities and investment decisions

Your Skills & Abilities (Required Qualifications)

• Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Analytics, or equivalent experience
• 6+ years in endpoint engineering, endpoint management, digital experience monitoring, IT operations, analytics, or related infrastructure roles
• Strong experience gathering telemetry and operational data from computers, endpoint management systems, and enterprise support platforms
• Experience creating comprehensive reports, dashboards, and presentations for engineering teams, operational stakeholders, and leadership audiences
• Strong analytical skills with the ability to identify patterns, trends, anomalies, and actionable insights from large or complex data sets
• Hands-on experience with enterprise endpoint ecosystems, including Windows, macOS, Linux, and/or VDI in a medium-to-large enterprise environment
• Experience with scripting and automation using tools such as PowerShell, Python, SQL, or similar technologies
• Demonstrated ability to translate technical data into operational recommendations, executive summaries, and measurable engineering actions
• Excellent communication skills and comfort working across engineering, security, infrastructure, operations, and business partners
• Solid background in: Endpoint telemetry collection and data correlation; Reporting, dashboarding, and data visualization practices; Endpoint management platforms and device compliance reporting; Root cause analysis using operational and endpoint experience data; Automation of recurring data collection, reporting, or remediation workflows

Preferred Qualifications

• Experience with digital employee experience, endpoint analytics, or experience monitoring platforms
• Experience with enterprise reporting and visualization tools such as Power BI, Tableau, or similar platforms
• Experience integrating data across endpoint management, asset, service management, monitoring, and support ecosystems
• Familiarity with modern endpoint management practices in large-scale enterprise environments
• Experience building automation that supports proactive detection, reporting, or remediation of endpoint issues
• Understanding of security, compliance, and data governance considerations related to endpoint telemetry
• Familiarity with Zero Trust principles and how endpoint health and device posture support access and security decisions
• Experience supporting executive reporting, operational reviews, or service performance management

What Success Looks Like

• Engineering teams have clear, trusted visibility into the health and digital experience of GM end user endpoints
• Leadership has concise, meaningful reporting on endpoint reliability, experience trends, risks, and opportunities
• Endpoint issues are identified earlier through telemetry and trend analysis rather than through reactive escalations alone
• Manual reporting effort is reduced through automation and repeatable data pipelines
• Platform changes and engineering investments are measured consistently with clear outcomes and supporting data
• A measurable improvement in endpoint experience: devices are more stable, performance issues are surfaced earlier, and end users experience fewer disruptions

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