Knowledge Graph Architect information
See Dallas, TX salary details
$59.9K - $73.9K
4% of jobs
$73.9K - $87.8K
17% of jobs
$88.7K is the 25th percentile. Wages below this are outliers.
$87.8K - $101.8K
17% of jobs
The median wage is $113.2K / yr.
$101.8K - $115.7K
11% of jobs
$115.7K - $129.6K
4% of jobs
$129.6K - $143.6K
4% of jobs
$143.6K - $157.5K
3% of jobs
$162.3K is the 75th percentile. Wages above this are outliers.
$157.5K - $171.5K
33% of jobs
$171.5K - $185.4K
1% of jobs
$185.4K - $199.3K
2% of jobs
How much do knowledge graph architect jobs pay per year?
As of Aug 14, 2026, the average yearly pay for knowledge graph architect in Dallas, TX is $127,370.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,000.00 and $164,200.00 per year, depending on experience, location, and employer.
Knowledge Graph Architects are professionals who design, develop, and maintain knowledge graphs—data structures that organize information into interconnected entities and relationships. They combine expertise in data modeling, semantic technologies, and ontologies to enable advanced data integration, search, and analytics within organizations. Their work helps businesses extract meaningful insights from complex datasets by structuring information in ways that are both machine-readable and semantically rich.
Knowledge Graph Architects often encounter challenges related to data heterogeneity, including varying data formats, inconsistent naming conventions, and differing semantics across multiple systems. Successfully integrating these disparate data sources requires designing robust ontologies, mapping relationships, and resolving conflicts to ensure data consistency and usability. Collaboration with domain experts, data engineers, and business stakeholders is essential to align technical solutions with business needs, making strong communication skills and adaptability crucial in this role.
To thrive as a Knowledge Graph Architect, you need expertise in data modeling, semantic technologies, graph databases, and a strong background in computer science or information systems. Familiarity with tools like RDF, SPARQL, OWL, Neo4j, and experience with data integration platforms or cloud-based data services is highly valuable. Strong problem-solving, communication, and stakeholder management skills are essential to translate complex data needs into scalable knowledge graph solutions. These competencies enable effective design, implementation, and maintenance of knowledge graphs, which are critical for deriving actionable insights from complex data landscapes.
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