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Neo4J Developer Jobs in Texas (NOW HIRING)

Infovision

AI Engineer

Dallas, TX · On-site

... Neo4j, RDF, SPARQL, and graph-based reasoning for AI applications Strong background in Data Engineering -- ETL/ELT pipelines, data modeling, and orchestration tools (Airflow, Prefect, or Dagster ...

InfoVision, Inc.

AI Engineer

Dallas, TX · On-site

Proficient in Knowledge Graph design and implementation - Neo4j, RDF, SPARQL, and graph-based reasoning for AI applications * Strong background in Data Engineering - ETL/ELT pipelines, data modeling ...

CareSet Systems

Mid-level SQL PHP Developer

Houston, TX · On-site

$65K/yr

Have experience with graph databases like neo4j * Hadoop/PIG would be lovely * MongoDB is great * Data science, statistics and/or graph analysis would be great as well Additional Information ...

CareSet Systems

Mid-level SQL PHP Developer

Houston, TX · On-site

$65K/yr

Have experience with graph databases like neo4j * Hadoop/PIG would be lovely * MongoDB is great * Data science, statistics and/or graph analysis would be great as well Additional Information ...

Photon

Senior Java Developer - AI/ML

Dallas, TX · On-site

$119K - $155K/yr

Senior Java Developer AI/LLM Solutions Location: Dallas, TX (Onsite) About the Role We are seeking ... Neo4j or Knowledge Graphs * Apache Spark * Airflow * Elasticsearch/OpenSearch * Redis * Temporal.io

Cotality

Principal, Data Engineer

Dallas, TX

... such as Neo4j and Google Spanner. Familiarity with orchestration tools like Apache Airflow is ... In this role, you will serve as a lead (anchor) engineer, driving the design and delivery of ...

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Neo4J Developer information

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$43.1K

$110K

$135.9K

How much do neo4j developer jobs pay per year?

As of Aug 16, 2026, the average yearly pay for neo4j developer in Texas is $110,015.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,134.00 and $131,035.00 per year, depending on experience, location, and employer.

What is a Neo4j developer?

A Neo4J Developer is responsible for designing, developing, and optimizing graph database solutions using Neo4J. They work on data modeling, Cypher query optimization, and integrating Neo4J with applications. Their role involves understanding relationships between data, improving performance, and ensuring scalability. Additionally, they may collaborate with data scientists and engineers to leverage graph analytics for insights.

What are some common challenges faced by Neo4j developers, and how can they be addressed?

Neo4J Developers often encounter challenges such as optimizing complex queries for large datasets, ensuring data consistency, and integrating Neo4J with other systems or applications. Addressing these challenges typically involves a deep understanding of graph database performance tuning, designing scalable data models, and staying current with Neo4J updates and best practices. Collaborating closely with backend engineers, data scientists, and DevOps teams is also key to overcoming integration and architectural hurdles. With experience, many Neo4J Developers develop strong troubleshooting skills and may progress into senior developer or data architect roles.

What are the key skills and qualifications needed to thrive as a Neo4j developer?

To thrive as a Neo4J Developer, you need a solid background in graph database concepts, data modeling, Cypher query language, and software development (often with Java, Python, or JavaScript). Experience with Neo4J tools and platforms, as well as relevant certifications like Neo4J Certified Professional, are highly valued by employers. Strong problem-solving abilities, effective communication, and the ability to work both independently and collaboratively are important soft skills. These competencies ensure you can efficiently design, implement, and optimize graph-based solutions that support complex data relationships within modern business applications.

What are the most commonly searched types of Neo4J Developer jobs in Texas?

The most popular types of Neo4J Developer jobs in Texas are:

What are popular job titles related to Neo4J Developer jobs in Texas?

For Neo4J Developer jobs in Texas, the most frequently searched job titles are:

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Neo4J Developer jobs near you
Infographic showing various Neo4J Developer job openings in Texas as of August 2026, with employment types broken down into 100% Contract. Highlights an 100% In-person job distribution, with an average salary of $110,015 per year, or $52.9 per hour.

Sr. Consultant Machine Learning & Knowledge Graph Engineer

Dell, Inc.

Round Rock, TX • On-site

$97K - $133K/yr

Full-time

Posted 26 days ago

Job description


Sr. Consultant Machine Learning & Knowledge Graph Engineer
Data Science is all about breaking new ground to enable businesses to answer their most urgent questions. Pioneering massively parallel data-intensive analytic processing, our mission is to develop a whole new approach to generating meaning and value from petabyte-scale data sets and shape brand new methodologies, tools, statistical methods and models. What's more, we are in collaboration with leading academics, industry experts and highly skilled engineers to equip our customers to generate sophisticated new insights from the biggest of big data.
Join us to do the best work of your career and make a profound impact as Sr. Consultant Machine Learning & Knowledge Graph Engineer on our growing and dynamic team in Round Rock, Texas.
What you'll achieve
Lead the architecture, development, and deployment of enterprise scale ML solutions across Dell's global ecosystem. Drive MLOps standards, build production grade ML services, and collaborate across engineering, product, and platform teams to enable AI at scale. Scale ML solutions across Dell's global ecosystem. As a Sr. Consultant Machine Learning & Knowledge Graph Engineer, you will play a pivotal role in advancing our AI and ML capabilities and creating Enterprise wide KG marketplace and Ontology layouts. This is a high-impact, enterprise-level technical leadership position responsible for defining and executing Dell's graph data strategy. You will architect production-grade Knowledge Graph platforms, design semantic data layers that power Agentic AI, and drive the convergence of graph technologies with large-scale data engineering ecosystems. This role demands a rare combination of deep graph expertise, distributed systems mastery, and strategic business influence.
You will
  • Knowledge Graph Architecture and Delivery: Design, build, and scale enterprise Knowledge Graph platforms using Neo4j and/or Stardog, establishing graph-native data models that enable entity resolution, relationship discovery, and semantic reasoning across business domains. Ontology and Semantic Layer Engineering: Define and govern enterprise ontologies (OWL 2), taxonomies, and semantic schemas that provide a unified, machine-interpretable view of Dell's data assets, ensuring consistency, reusability, and inferencing capability

  • Graph-Powered Agentic AI Infrastructure: Architect graph-backed Retrieval-Augmented Generation (RAG) systems, tool-calling interfaces, and dynamic prompt-to-graph query pipelines that fuel autonomous AI agent decision-making with deterministic, explainable knowledge. Data Virtualization and Federation: Lead the design of virtualized graph layers using Stardog Virtual Graphs or equivalent federation patterns, enabling real-time querying across SQL, NoSQL, and streaming data sources without mass ETL

  • Graph Data Science and Analytics: Operationalize advanced graph algorithms - community detection, centrality analysis, node embeddings (Node2Vec, FastRP), link prediction - using Neo4j GDS or equivalent libraries to extract actionable intelligence from connected data. Real-Time Graph Ingestion and Streaming: Design high-throughput, low-latency graph ingestion pipelines integrating Kafka, Spark Structured Streaming, and graph-native CDC mechanisms to maintain continuously updated knowledge representations

  • Enterprise Graph Governance: Establish comprehensive graph data governance frameworks including SHACL/SHEX constraint validation, RBAC-based graph security models, data lineage tracking, and ontology versioning strategies. Cross-Functional Strategic Partnership: Collaborate with Principal Data Scientists, AI/ML platform teams, product leaders, and executive stakeholders to identify high-value graph use cases and translate complex business problems into graph-solvable architectures

  • Technology Evaluation and Innovation: Continuously evaluate emerging graph technologies (GQL/ISO standards, vector-graph hybrid search, graph neural networks, LLM-to-graph interfaces) and provide executive-level recommendations on adoption. Mentorship and Engineering Culture: Serve as the technical anchor and mentor for Senior Advisors, Staff Engineers, and tech leads, cultivating deep graph expertise across the organization and driving a culture of engineering excellence and innovation

Take the First Step Towards Your Dream Career
Every Dell Technologies team member brings something unique to the table. Here's what we are looking for with this role:
Essential Requirements:
  • Graph Architecture Mastery: Extensive hands-on experience designing and operating production-grade graph systems using Neo4j (Cypher, GDS, APOC, AuraDB, Causal Clustering) and/or Stardog (SPARQL, OWL 2 reasoning, Virtual Graphs, SHACL validation) along with Ontology and Semantic Modeling: Proven expertise in enterprise ontology engineering - OWL 2 profiles, RDF/RDFS, SKOS taxonomies, property graph modeling patterns, and schema evolution strategies at scale

  • Agentic AI and RAG Engineering: Deep practical understanding of building graph-backed data environments for autonomous AI agents, including knowledge retrieval pipelines, tool-calling orchestration, dynamic SPARQL/Cypher generation from natural language, and hybrid vector-graph search architectures

  • Distributed Systems and Data Scale: Expert-level command over PySpark, Kafka, data lakehouses (Apache Iceberg, Delta Lake), and enterprise orchestration (Airflow), with proven ability to integrate these with graph ecosystems and programming and query proficiency: Advanced fluency in Python, SQL, Cypher, and SPARQL, with strong software engineering practices (CI/CD, testing, version control, containerization)

  • Graph Data Science: Hands-on experience operationalizing graph algorithms - PageRank, Louvain, Label Propagation, node embedding techniques - and integrating graph-derived features into downstream ML/AI pipelines

  • Experience: 12+ years of progressive experience in data engineering, graph architecture, and cloud-native platform delivery, with at least 4+ years focused specifically on Knowledge Graph or semantic technology initiatives at enterprise scale

  • Strategic Leadership: Exceptional communication, advisory, and stakeholder-management skills, with a demonstrated history of driving large-scale technical transformations and influencing cross-functional technology strategy

Desirable Requirements
  • PhD or Master's degree in Technology, Computer Science, Machine Learning or equivalent quantitative field
  • Experience in data mesh or data fabric architectures with graph as the metadata backbone.
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About DELL

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Dell Technologies helps organizations and individuals build a brighter digital tomorrow. Our company is made up of more than 150,000 people, located in over 180 locations around the world. We're proud to be a diverse and inclusive team and have an endless passion for our mission to drive human progress.

Industry

Computer and computer peripheral equipment and software wholesalers

Company size

10,000+ Employees

Headquarters location

Round Rock, TX, US

Year founded

1984

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