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Graph Database Jobs in Florida (NOW HIRING)

Big Data Engineer Principal

Orlando, FL

$106.90K - $128.40K/yr

Semantic modeling and Ontology to support future graph database implementation. * Well Rounded understanding of metadata and its implementation in a data catalog. * Develop trusted authoritative ...

Big Data Engineer Principal

Orlando, FL

$52 - $68.75/hr

Semantic modeling and Ontology to support future graph database implementation. * Well Rounded understanding of metadata and its implementation in a data catalog. * Develop trusted authoritative ...

Big Data Engineer Principal

Orlando, FL · On-site

$106.90K - $128.40K/yr

Semantic modeling and Ontology to support future graph database implementation. * Well Rounded understanding of metadata and its implementation in a data catalog. * Develop trusted authoritative ...

Exposure to graph databases (Neo4j/Cypher) or cloud data platforms (Snowflake, Azure Fabric) is a plus. Version control (Git) required. • AI & LLM Integration: Demonstrated curiosity about or ...

CyberArk Senior Consultant

Miami, FL · On-site

$52 - $68.75/hr

... graph databases such as Neo4j or Memgraph. • Familiarity with build tools such as Maven or Gradle. • Experience with Bootstrap, jQuery, or JSP in legacy or mixed-technology environments. • ...

Deep knowledge of logic and proof techniques, set theory, combinatorics, graph theory, number ... Emphasizes logical reasoning and rigorous argumentation, connecting discrete structures to database ...

Deep knowledge of logic and proof techniques, set theory, combinatorics, graph theory, number ... Emphasizes logical reasoning and rigorous argumentation, connecting discrete structures to database ...

Deep knowledge of logic and proof techniques, set theory, combinatorics, graph theory, number ... Emphasizes logical reasoning and rigorous argumentation, connecting discrete structures to database ...

Deep knowledge of logic and proof techniques, set theory, combinatorics, graph theory, number ... Emphasizes logical reasoning and rigorous argumentation, connecting discrete structures to database ...

Deep knowledge of logic and proof techniques, set theory, combinatorics, graph theory, number ... Emphasizes logical reasoning and rigorous argumentation, connecting discrete structures to database ...

Deep knowledge of logic and proof techniques, set theory, combinatorics, graph theory, number ... Emphasizes logical reasoning and rigorous argumentation, connecting discrete structures to database ...

Deep knowledge of logic and proof techniques, set theory, combinatorics, graph theory, number ... Emphasizes logical reasoning and rigorous argumentation, connecting discrete structures to database ...

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Graph Database information

See Florida salary details

$19

$39

$60

How much do graph database jobs pay per hour?

As of May 31, 2026, the average hourly pay for graph database in Florida is $39.70, according to ZipRecruiter salary data. Most workers in this role earn between $32.50 and $44.90 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.

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 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 Florida? The most popular types of Graph Database jobs in Florida are:
What job categories do people searching Graph Database jobs in Florida look for? The top searched job categories for Graph Database jobs in Florida are:
Infographic showing various Graph Database job openings in Florida as of May 2026, with employment types broken down into 1% As Needed, 45% Full Time, 12% Part Time, 3% Temporary, 38% Contract, and 1% Nights. Highlights an 21% Physical, 25% Hybrid, and 54% Remote job distribution, with an average salary of $82,567 per year, or $39.7 per hour.
Big Data Engineer Principal

Big Data Engineer Principal

SAIC

Orlando, FL

$106.90K - $128.40K/yr

Full-time

Posted 24 days ago


SAIC rating

7.8

Company rating: 7.8 out of 10

Based on 78 frontline employees who took The Breakroom Quiz

68th of 203 rated it services


Job description

Job ID: 2612938

Location: Orlando, FL, US

Date Posted: 2026-05-26

Category: Information Technology

Subcategory: Big Data Engineer

Schedule: Full-Time

Shift: Day Job

Travel: Yes - 10% of the time

Minimum Clearance Required: Secret

Clearance Level Must Be Able to Obtain: None

Potential for Remote Work: ORA_ON_SITE


Description

SAIC is seeking an experienced Big Data / Parametric Data Engineer to support an Air Force program out of Orlando, FL.

(This is an onsite position, with no option for remote work).

You must possess an Active Security Clearance to qualify for this position.

Job Duties / Responsibilities:

  • Ensure parametric datasets established for supporting training and readiness comply with the Department of the Air Force (DAF) Data Fabric initiatives as well as the DoD Data Strategy, DAF I-Plan, and AFAMS Data Concept Plan.
  • Provision parametric data services for Air Force Training Simulation Centers:
  • Leverage commercial technology to the maximum extent possible and shall align work with the existing DAF Data Fabric initiative, to include the mandatory use of one of the top five big data platforms: Envision, VAULT, ELICSAR, Unified Data Library, and SIGNUS.
  • Test data services for the community to access parametric data addressing an agreed upon Source of Truth (ASoT) Dataset for the Training Simulation Centers.
  • Provision data services for the community to access parametric data; Make data: Visible, Accessible, Usable, Linked, Trusted, Interoperable, and Secure for the AF Training Simulation Centers.
  • Support tactical data training requirements:
    • Support government training data efforts at the tactical level to meet integrated training needs.
    • Support joint/coalition interoperability data efforts to enhance training capabilities.

Qualifications

  • Bachelor's and nine (9), Masters and seven (7); or relevant years of experience in lieu of degree.
  • Demonstrable expertise or be a subject matter expert in DoD wide parametric data.
  • Data access capability using SQL and python.
  • Knowledge of commercial parametric data sources.
  • Experience using military parametric data in synthetic environments.
  • Ability to train others on the usage of parametric data.
  • Data Engineering skill building ETL (Extract-Transform-Load) pipelines to support self-service data capability to the developer.
  • Data Interoperability acumen focused on making many siloed data systems work as one.
  • Semantic modeling and Ontology to support future graph database implementation.
  • Well Rounded understanding of metadata and its implementation in a data catalog.
  • Develop trusted authoritative datasets and data products that support varied use-cases.
  • Understanding the deployment of air-gapped data systems.
  • Solid understanding of data fabric and data mesh design and architectures.
  • Wide understanding of legacy and current data systems.
  • US Citizen and an Active Secret Security Clearance.

Desired Experience:

  • Data Expert(s) with demonstrated proficiency (e.g., Data Analyst, Data Scientist, Data Engineer, etc.) and the most current Information Technology (IT) and IT/Data mecca experience (e.g., Silicon Valley, Austin, Seattle, Colorado Springs).
  • Individual(s) must have previous experience in designing/building data stores or connecting via existing commercial Application Programming Interfaces (APIs) to commercially available data stores and must have previous experience in planning data lakes to transform and load legacy datasets to enterprise datasets for cloud environments.
  • Individual(s) must be familiar with the DAF’s Data Fabric effort with one of the top five big data platforms: Envision, VAULT, ELICSAR, Unified Data Library, and SIGNUS as starting points for DAF enterprise data transport, data mapping, data prep, and/or data aggregation effort.
  • Individual(s) must be Certified Data Management Professionals (CDMP) accredited by the Data Management Association (DAMA) International.
  • Individual(s) shall have first-hand experience with data services platforms to control data assets and guide the aggregation of large and disparate collections of enterprise data.
  • Individual(s) must have hands-on experience demonstrating, within one project, the ability to handle large data assets across various commercial industries that created new opportunities previously not realized. 


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