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$73

How much do knowledge engineer jobs pay per hour?

As of Sep 13, 2026, the average hourly pay for knowledge engineer in the United States is $47.61, according to ZipRecruiter salary data. Most workers in this role earn between $39.18 and $57.69 per hour, depending on experience, location, and employer.

What is a knowledge engineer?

A knowledge engineer works with data and computer systems with the goal of making the technology imitate human thought processes to solve problems that typically require expertise. Working in a sector of artificial intelligence within the information technology field, a knowledge engineer looks at everyday processes and determines what course of thought a human takes to make a decision or begin an activity. They then create computer systems reliant on this extensive data to guide a machine to simulate human cognition and problem-solving. The data validation process is a vital aspect of a knowledge engineer’s job. They must gather an accurate understanding of the tasks at hand and ensure that the data meets specific standards.

What are the key skills and qualifications needed to thrive as a knowledge engineer, and why are they important?

To thrive as a Knowledge Engineer, you need a solid background in computer science, logic, and knowledge representation, often supported by a relevant degree. Familiarity with semantic web technologies, ontology development tools (like Protégé), and knowledge management systems is typically required. Analytical thinking, attention to detail, and strong communication skills help you effectively translate complex information into structured, usable formats. These capabilities ensure that knowledge systems are accurate, interoperable, and valuable for organizational decision-making.

What are some common challenges knowledge engineers face when collaborating with subject matter experts (SMEs)?

Knowledge Engineers often work closely with subject matter experts to extract and formalize complex domain knowledge into structured formats for systems like knowledge bases or AI applications. One common challenge is bridging the communication gap, as SMEs may use specialized jargon or have implicit knowledge that's difficult to articulate. Ensuring accuracy while translating this expertise into machine-readable forms requires patience, active listening, and iterative feedback. Building strong relationships and developing effective questioning techniques are essential for overcoming these challenges and delivering high-quality knowledge models.

What is the difference between Knowledge Engineer vs Data Scientist?

AspectKnowledge EngineerData Scientist
Required CredentialsBachelor's or Master's in Computer Science, AI, or related fields; knowledge of ontologies and knowledge basesBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in programming, statistics, and data analysis
Work EnvironmentTypically in AI development teams, focusing on knowledge systems and expert systemsOften in analytics teams, working with large datasets and predictive modeling
Employer & Industry UsageUsed in AI, robotics, and enterprise knowledge managementCommon in tech, finance, healthcare, and marketing sectors

While both roles involve working with data and information, Knowledge Engineers focus on structuring and encoding knowledge for AI systems, whereas Data Scientists analyze data to extract insights and build predictive models. Their skills and tools differ, but both are essential in data-driven industries.

How much do knowledge engineers make?

Knowledge engineers typically earn a median annual salary between $80,000 and $120,000, depending on experience, education, and industry. Senior roles or those with specialized skills in artificial intelligence and data management can earn higher salaries, often exceeding $150,000. Compensation may also include benefits such as bonuses and stock options.
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Knowledge Engineer jobs near you
Infographic showing various Knowledge Engineer job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 79% Full Time, 18% Part Time, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $99,026 per year, or $47.6 per hour.

Omnissa Intelligence Specialist / DEX Analytics Engineer

Belleville, NJ • On-site

PB consulting
See more jobs at PB consultingexternal

Full-time

Posted 12 days ago

Job description

We are seeking an experienced Omnissa Intelligence Specialist / DEX Analytics Engineer to transform endpoint, application, and virtual desktop telemetry into actionable insights and automated remediation. The role focuses on Digital Employee Experience (DEX) analytics, dashboard development, telemetry correlation, workflow automation, and proactive IT operations across Omnissa digital workspace environments.

Required Skills

2+ years of hands-on production experience with Omnissa Intelligence / Workspace ONE Intelligence.
Working knowledge of Workspace ONE UEM and/or Omnissa Horizon.
Experience developing and maintaining Omnissa Intelligence dashboards, reports, and analytics.
Hands-on experience with Freestyle Orchestrator or equivalent low-code/no-code automation platforms.
Strong understanding of DEX/EUC concepts, including device compliance, application performance, VDI session health, and user experience scoring.
Experience correlating telemetry across endpoints, applications, network, VDI, and security tools.
Strong troubleshooting and Root Cause Analysis (RCA) skills.
Experience integrating analytics insights with ITSM/ticketing workflows.

Roles and Responsibilities

Configure and maintain Omnissa Intelligence dashboards, reports, and DEX analytics for device health, application performance, compliance, and user experience.
Develop automation workflows using Freestyle Orchestrator to perform remediation actions such as configuration changes, patching, and ticket creation.
Analyze and correlate telemetry from endpoints, applications, VDI sessions, networks, and security platforms to identify recurring issues.
Integrate DEX insights with ITSM platforms and support workflows to improve incident resolution and operational efficiency.
Configure and optimize experience and sentiment scoring to accurately measure employee experience.
Integrate supported third-party security and risk platforms for unified visibility and risk scoring.
Use AI-assisted analytics/query capabilities to accelerate data exploration and troubleshooting.
Monitor KPIs such as device compliance, application crash rates, boot/login times, VDI health, and DEX scores.
Create technical documentation, data-flow diagrams, and operational runbooks.
Train support teams on interpreting dashboards, analytics, and remediation workflows.
Identify opportunities to improve employee experience through proactive monitoring, automation, and remediation.

Preferred Skills

Experience integrating security platforms such as Lookout Mobile Threat Defense (MTD) or Netskope CASB.
Experience with ServiceNow or other ITSM platforms and Workspace ONE ITSM integrations.
Omnissa/VMware certifications in Digital Workspace, UEM, or Horizon.
Scripting experience with PowerShell or Python.
Experience with advanced DEX analytics, automation, and proactive remediation.

Apply