1

Graph Database Jobs in Texas (NOW HIRING)

Neo4J developer

Austin, TX · On-site

$50.50 - $65.50/hr

Designing, implementing, and optimizing graph-based solutions using Neo4j, collaborating with stakeholders, and potentially providing technical expertise on graph database best practices. * Working ...

Senior Data Engineer

Roanoke, TX · Hybrid

$101K - $138K/yr

... Graph database), Hadoop ecosystem (Hadoop, Hive, Sqoop, Flume, HBase), API and in-memory technologies. * Strong knowledge of developing highly scalable distributed systems using Open source ...

Principal Data Architect

Grapevine, TX · On-site

$140K - $150K/yr

Soni's client is seeking a Principal Data Architect to lead enterprise-wide data architecture strategy across relational, NoSQL, vector, and graph database ecosystems. This is the most senior ...

... graph database (Spanner Graph, Neo4j, or similar) including schema design and query writing. - Strong experience with Google Cloud Platform (GCP) - Vertex AI, Cloud Run, BigQuery, Pub/Sub, Load ...

You'll work hands-on across the technology stack, from graph databases and semantic modeling to NLP pipelines and content delivery systems, while influencing architecture decisions and engineering ...

Python Developer

Irving, TX · On-site

$48.25 - $66.50/hr

Hands on experience integrating with graphql & graph database * Good understanding and setting up Neo4J database * Hands-on development experience including writing and testing code, debugging ...

Data Engineer - AWS, Python, SQL

Roanoke, TX

$109K - $132K/yr

... Graph database), Hadoop ecosystem (Hadoop, Hive, Sqoop, Flume, HBase), API and in-memory technologies. Strong knowledge of developing highly scalable distributed systems using Open-source ...

Implement and maintain MCP server integration with tools for vector store operations (upsert, search), Neo4j graph database queries, and file metadata lookup. Platform Development * Design, build ...

Expertise in Relational (AWS RDS, Oracle & Postgres) and NoSQL databases (DynamoDB, Elastic search, Graph database) and in-memory technologies (Elastic Cache, Redis etc..) * Experience developing ...

Expertise in Relational (AWS RDS, Oracle & Postgres) and NoSQL databases (DynamoDB, Elastic search, Graph database) and in-memory technologies (Elastic Cache, Redis etc..) * Experience developing ...

Senior AI Developer

Houston, TX · On-site

$52 - $68.75/hr

Responsibilities : • Helps set technical direction for AI/ML -- evaluates models, frameworks, vector stores, graph databases, evaluation tooling, and orchestration patterns; makes recommendations ...

next page

Showing results 1-20

Graph Database information

See Texas salary details

$24

$49

$75

How much do graph database jobs pay per hour?

As of Jun 20, 2026, the average hourly pay for graph database in Texas is $49.49, according to ZipRecruiter salary data. Most workers in this role earn between $40.53 and $56.01 per hour, depending on experience, location, and employer.

What is a Graph Database job?

A Graph Database job typically involves working with graph-based database technologies such as Neo4j, ArangoDB, or Amazon Neptune. Professionals in this role design, implement, and optimize graph database models to efficiently store and retrieve complex relationships between data points. Common responsibilities include data modeling, query optimization using graph query languages (e.g., Cypher, Gremlin), and integrating graph databases into larger data ecosystems. These roles are often found in industries like fraud detection, social networking, and recommendation systems, where understanding relationships between data is crucial.

Are graph databases the future?

Graph database professionals are in demand as these databases are increasingly used for complex data relationships in areas like social networks, fraud detection, and recommendation systems. Skills in query languages such as Cypher and knowledge of data modeling are valuable for roles in this field, which is expected to grow with the expansion of data-driven applications.

What are the top 5 graph databases?

The top five graph databases widely used in the industry are Neo4j, Amazon Neptune, Microsoft Azure Cosmos DB, TigerGraph, and ArangoDB. These databases are known for their scalability, query languages like Cypher or Gremlin, and suitability for complex relationship data. Skills in graph modeling and query optimization are valuable for roles involving graph database management.

Is Neo4j better than SQL?

As a graph database, Neo4j is optimized for managing highly connected data and complex relationships, making it more suitable than SQL for certain use cases like social networks or recommendation engines. SQL databases excel at structured, tabular data and transactional consistency but are less efficient for relationship-heavy queries. The choice depends on the specific data model and application requirements.

What are the key skills and qualifications needed to thrive in the Graph Database position, and why are they important?

To thrive as a Graph Database Engineer, you need expertise in data modeling, query languages such as Cypher or Gremlin, and a solid understanding of graph theory and database architectures. Familiarity with graph database platforms like Neo4j, Amazon Neptune, or TigerGraph, as well as certifications in relevant technologies, are highly valued. Strong problem-solving skills, attention to detail, and effective communication are essential soft skills for collaborating with development and analytics teams. These competencies are vital for designing efficient graph data solutions, optimizing performance, and supporting business insights through connected data analysis.

What is the salary of graph database developer?

The salary of a graph database developer typically ranges from $80,000 to $130,000 annually, depending on experience, location, and specific skills such as proficiency with graph database tools like Neo4j or Amazon Neptune. Senior roles or those with specialized expertise can earn higher compensation, often exceeding $150,000. Certifications and industry demand also influence salary levels.

What are some common challenges faced by professionals working with graph databases?

One common challenge when working with graph databases is efficiently modeling highly connected data structures to optimize for both query performance and scalability. Professionals must continuously evaluate indexing strategies and traversal queries to prevent bottlenecks as datasets grow. Another challenge is integrating graph databases with existing data pipelines or relational systems, which often requires specialized knowledge. However, these challenges offer opportunities to innovate and collaborate with cross-functional teams to deliver powerful solutions for complex data relationships.

What are the most commonly searched types of Graph Database jobs in Texas? The most popular types of Graph Database jobs in Texas are:
What job categories do people searching Graph Database jobs in Texas look for? The top searched job categories for Graph Database jobs in Texas are:
What cities in Texas are hiring for Graph Database jobs? Cities in Texas with the most Graph Database job openings:
Infographic showing various Graph Database job openings in Texas as of June 2026, with employment types broken down into 69% Full Time, 15% Part Time, 4% Temporary, and 12% Contract. Highlights an 53% Physical, 4% Hybrid, and 43% Remote job distribution, with an average salary of $102,937 per year, or $49.5 per hour.

Other

Posted 3 days ago


Job description

Job Title

Skill: At least 3 years of experience on the following:

  • Machine Learning – Decision Trees, Random Forests, Rule Mining, Clustering, PCA, Support Vector Machine, Ensemble techniques
  • Deep Learning - Neural networks, multilayer perceptron, word embeddings, categorical embedding, RNN and LSTM, word2vec, encoder/decoder models, attention and transformer models, transfer learning (ULMFiT), foundation models from Azure Open AI
  • Database - Snowflake, Oracle, Graph database
  • Programming & Scripting - Python, R, Unix-Shell scripting, PySpark