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Contract Knowledge Graph Software Engineer Jobs (NOW HIRING)

Geico

Staff Software Engineer (HYBRID)

Bethesda, MD · On-site

GEICO is seeking an experienced Staff Software Engineer to join our Knowledge Graph and Content Generation engineering group. This is a high-impact team focused on scaling GEICO's intelligent content ...

Geico

Staff Software Engineer (HYBRID)

Dallas, TX · On-site

GEICO is seeking an experienced Staff Software Engineer to join our Knowledge Graph and Content Generation engineering group. This is a high-impact team focused on scaling GEICO's intelligent content ...

Geico

Staff Software Engineer (HYBRID)

Seattle, WA · On-site

GEICO is seeking an experienced Staff Software Engineer to join our Knowledge Graph and Content Generation engineering group. This is a high-impact team focused on scaling GEICO's intelligent content ...

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All JobsContract Knowledge Graph Software Engineer Jobs

Contract Knowledge Graph Software Engineer information

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$63.5K

$147.5K

$205.5K

How much do contract knowledge graph software engineer jobs pay per year?

As of Jul 31, 2026, the average yearly pay for contract knowledge graph software engineer in the United States is $147,524.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,000.00 and $173,000.00 per year, depending on experience, location, and employer.

How does a Contract Knowledge Graph Software Engineer typically collaborate with data scientists and domain experts during a project?

As a Contract Knowledge Graph Software Engineer, you’ll often work closely with data scientists and domain experts to ensure that the knowledge graph accurately represents the underlying data and business logic. Collaboration usually involves regular meetings to clarify requirements, discuss data models, and review results. You may be tasked with translating complex domain concepts into graph structures, while also providing feedback on data quality and integration challenges. This cross-functional teamwork ensures that the final product meets both technical standards and business needs.

What is the difference between Contract Knowledge Graph Software Engineer vs Contract Data Engineer?

AspectContract Knowledge Graph Software EngineerContract Data Engineer
Required CredentialsBachelor's in CS or related, knowledge of graph databases, programming skillsBachelor's in CS, experience with data pipelines, SQL, and cloud platforms
Work EnvironmentTech companies, consulting firms, project-based rolesData-focused teams, cloud environments, analytics projects
Industry UsageAI, semantic web, knowledge managementData warehousing, big data, analytics

The Contract Knowledge Graph Software Engineer primarily focuses on developing and maintaining knowledge graphs using graph databases and semantic technologies, while the Contract Data Engineer concentrates on building data pipelines, managing large datasets, and supporting analytics. Both roles require strong programming skills and are often found in tech-driven industries, but they serve different core functions within data and knowledge management ecosystems.

What is a Contract Knowledge Graph Software Engineer?

A Contract Knowledge Graph Software Engineer is a professional who specializes in designing, developing, and maintaining knowledge graphs on a contract basis. Knowledge graphs are data structures that represent relationships between entities, enabling more effective data integration and semantic search. These engineers often work with graph databases, semantic web technologies, and ontologies to help organizations manage and leverage complex data. Their contract role means they are typically hired for specific projects or fixed periods rather than as permanent employees.

What are the key skills and qualifications needed to thrive as a Contract Knowledge Graph Software Engineer, and why are they important?

To thrive as a Contract Knowledge Graph Software Engineer, you need a strong background in computer science, proficiency in graph databases (such as Neo4j or Amazon Neptune), and experience with knowledge representation and data modeling. Familiarity with programming languages like Python or Java, as well as tools for semantic web technologies (RDF, SPARQL), is typically required. Strong problem-solving skills, adaptability, and effective collaboration are essential soft skills in this role. These competencies ensure efficient design and implementation of complex knowledge graphs, enabling organizations to unlock valuable insights from their data.
What cities are hiring for Contract Knowledge Graph Software Engineer jobs? Cities with the most Contract Knowledge Graph Software Engineer job openings:
What are the most commonly searched types of Knowledge Graph Software Engineer jobs? The most popular types of Knowledge Graph Software Engineer jobs are:
What states have the most Contract Knowledge Graph Software Engineer jobs? States with the most job openings for Contract Knowledge Graph Software Engineer jobs include:
Contract Knowledge Graph Software Engineer jobs near you

Ontology Engineer-Knowledge Graph & Identity

Samba

San Francisco, CA • On-site, Remote

Full-time

Re-posted 23 days ago

Job description

Samba is a media intelligence company. We know what the world is watching, reading, and thinking about - in real time, at scale, across every screen. Our data exists with the consent of over a billion people, organized into the most complete picture of consumer attention ever built. The biggest brands in the world use that picture to make smarter decisions. We think it's the most interesting data asset on the planet, because it's the most culturally relevant. 

As an Ontology Engineer on Samba TV's Knowledge Graph & Identity team, you will build, maintain, and extend the knowledge graph schemas, derivation pipelines, and graph data models that underpin Samba's measurement and audience intelligence products. Working closely with the Senior Ontologist and peer data scientists, you will implement ontological frameworks in production, contribute to entity resolution and data enrichment pipelines, and help ensure the graph layer remains accurate, consistent, and production-ready.

This is a hands-on technical role. You are expected to write clean, production-quality Python and SPARQL, take ownership of well-scoped graph work streams, and grow your depth in semantic modeling under the guidance of senior team members.

This role reports to the Data Science Manager, Knowledge Graph & Identity.

What You'll Do:
Ontology Implementation & Validation

  • Implement and extend Samba's RDF/RDFS/OWL ontology schemas in the graph database - adding entity classes, properties, and constraints in a consistent, governed way under the direction of the Senior Ontologist

  • Build and maintain SHACL validation shapes for post-load graph consistency checks; identify and triage data quality and schema violations

  • Support ontology versioning, change log documentation, and consistency checking across schema updates

  • Write efficient, well-structured SPARQL queries and graph traversals to support downstream data science and product use cases

Event-to-Ontology Derivation Pipelines

  • Contribute to the event-to-ontology transformation and derivation layer - building PySpark/Databricks pipelines that aggregate raw TV viewership and web activity events into durable graph attributes (genre affinity, brand affinity, topic affinity, viewing summaries, lifecycle signals)

  • Implement derivation logic specified by the Senior Ontologist and data science team; validate outputs against SHACL shapes before graph load

  • Support incremental refresh and update logic aligned with the graph's batch refresh cadence

Technical Contribution

  • Write production-quality Python - clean, well-tested, documented, and reusable by teammates

  • Work with PySpark and Databricks to process and transform high-volume data as part of graph pipeline development

  • Apply embedding-based approaches (semantic similarity, vector search) to entity matching and ontology alignment tasks

  • Contribute to team tooling, documentation, and reusable components that improve knowledge graph development efficiency

Collaboration & Growth

  • Partner closely with data engineering on pipeline design, data quality, and incremental ingestion patterns feeding the materialized graph substrate

  • Participate in ontology design reviews and cross-functional working groups

  • Work with product and operations teams to understand use case requirements and translate them into graph schema updates

  • Actively develop expertise in W3C semantic web standards, RDF-native graph databases, and entity resolution under the guidance of the Senior Ontologist

Who You Are:
Must-Haves

  • 2-4 years of hands-on experience in knowledge graph development, semantic data modeling, ontology engineering, or a closely related field

  • Working knowledge of W3C semantic web standards: RDF, RDFS, OWL, and SPARQL - with practical experience querying or building in at least one triplestore or graph database

  • Familiarity with SHACL or equivalent constraint and validation frameworks for graph data quality

  • Strong Python skills - clean, readable, production-quality code with testing and documentation

  • Solid understanding of data modeling fundamentals - entity-relationship design, taxonomies, hierarchies, and how to represent complex real-world relationships in structured form

  • Familiarity with entity resolution or data matching concepts - understanding of why the same real-world entity appears under different identifiers across data sources

  • Bachelor's degree required in Computer Science, Information Science, Mathematics, or a related field; Master's preferred

  • Detail-oriented and proactive about flagging data quality issues and schema inconsistencies

Strongly Preferred

  • Hands-on experience with Amazon Neptune or Stardog - or equivalent RDF-native triplestore; exposure to data virtualization (Neptune Orion or Stardog Virtual Graphs) a plus

  • Working knowledge of PySpark and Databricks - particularly for large-scale event aggregation and transformation pipelines

  • Familiarity with embedding models, vector search, or semantic similarity - applied to entity matching, ontology alignment, or knowledge graph enrichment

  • Experience with LLM APIs or RAG-based approaches applied to information extraction, entity disambiguation, or schema mapping

  • Domain knowledge in media, entertainment, or ad tech - content metadata, advertising entities, TV viewership data, or audience/identity data

  • Exposure to identity resolution, probabilistic record linkage, or device graph approaches

$150,000 - $180,000 a year
Samba is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.  We strive to empower connection with one another, reflect the communities we serve, and tackle meaningful projects that make a real impact.
 
Samba may collect personal information directly from you, as a job applicant, Samba may also receive personal information from third parties, for example, in connection with a background, employment or reference check, in accordance with the applicable law. For further details, please see Samba's Applicant Privacy Policy. For residents of the EU , Samba Inc. is the data controller.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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