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Data Quality Jobs in Florida (NOW HIRING)

RELX

AI Data Analyst

Boca Raton, FL · On-site

Are you passionate about improving data quality and readiness to unlock the full potential of AI solutions? Do you enjoy collaborating across teams to ensure data is structured, governed, and usable ...

NAVA Software Solutions

Data Architect

Orlando, FL · On-site

$59.50 - $76.50/hr

Data Quality and Governance: Define and enforce data quality standards, data governance policies, and data security measures to ensure compliance with industry regulations and organizational data ...

Dlapiper

Data Engineer

Miami, FL · On-site

$109K - $131K/yr

Data Quality, Reliability & Operations * Identify, troubleshoot, and resolve data issues including data quality, integrity, latency, and security concerns; apply monitoring and operational best ...

Apex Informatics

Data Architect

Tallahassee, FL · On-site

$60.50 - $78/hr

... quality measures to ensure timeliness, accuracy, and completeness of production data. • Collaborate with development teams to automate and streamline ETL processes. • Provide best practices for ...

NextEra Energy

Principal Data Analyst

Juno Beach, FL · On-site

Position Specific Description The Principal Data Analyst is responsible for ensuring data quality, integrity, and compliance throughout NextEra Energy's ETRM transformation project and ongoing ...

NextEra Energy

Principal Data Analyst

Juno Beach, FL · On-site

Position Specific Description The Principal Data Analyst is responsible for ensuring data quality, integrity, and compliance throughout NextEra Energy's ETRM transformation project and ongoing ...

Ci

Data Engineering Manager

Miami, FL

Data QA operations . Implement automated QA analytics, reconciliations, and monitoring to ensure data integrity across enterprise platforms and enterprise data layer. Establish data quality ...

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All JobsData Quality JobsData Quality Jobs in Florida

Data Quality information

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How much do data quality jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for data quality in Florida is $30.96, according to ZipRecruiter salary data. Most workers in this role earn between $20.82 and $40.58 per hour, depending on experience, location, and employer.

Is data quality a good career?

Data quality is a valuable career path involving ensuring the accuracy, consistency, and reliability of data within organizations. Professionals in this field often work with data management tools, perform audits, and may pursue certifications like Certified Data Management Professional (CDMP). It offers opportunities across industries such as finance, healthcare, and technology with steady demand for skilled data quality specialists.

What are the key skills and qualifications needed to thrive in a data quality position, and why are they important?

To thrive in a Data Quality role, you need expertise in data analysis, attention to detail, knowledge of data governance, and often a bachelor's degree in a related field such as computer science or information systems. Familiarity with tools like SQL, data profiling software, and data quality management platforms, as well as certifications like CDMP (Certified Data Management Professional), is highly valued. Strong problem-solving abilities, effective communication, and a collaborative mindset help professionals excel in this position. These skills are crucial for ensuring accurate, reliable data that supports business decision-making and overall organizational efficiency.

What is a data quality?

A Data Quality job involves ensuring that data is accurate, consistent, and reliable for business use. Professionals in this role develop and enforce data quality standards, identify and resolve data discrepancies, and implement processes for data validation and cleansing. They often work with databases, data governance frameworks, and analytics teams to maintain high-quality data. This role is essential for organizations relying on data-driven decisions, as poor data quality can lead to incorrect insights and inefficiencies.

What are the typical challenges faced by someone working in a data quality role?

Professionals in Data Quality roles often encounter challenges such as identifying inconsistent data sources, addressing missing or inaccurate data, and maintaining data standards as systems and business requirements evolve. Working closely with IT, data analysts, and business stakeholders, Data Quality specialists must resolve data discrepancies while balancing the need for accuracy with project deadlines. These challenges require excellent analytical and troubleshooting skills, as well as the ability to communicate data issues clearly across teams. Overcoming these hurdles is key to ensuring data-driven decisions are based on trustworthy information.

What are the most commonly searched types of Data Quality jobs in Florida? The most popular types of Data Quality jobs in Florida are:
What are popular job titles related to Data Quality jobs in Florida? For Data Quality jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Data Quality jobs in Florida look for? The top searched job categories for Data Quality jobs in Florida are:
What cities in Florida are hiring for Data Quality jobs? Cities in Florida with the most Data Quality job openings:
Data Quality jobs near you
Infographic showing various Data Quality job openings in Florida as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 14% Part Time, 1% Temporary, 3% Contract, and 2% Nights. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $64,407 per year, or $31 per hour.

AI Data Analyst

RELX

Boca Raton, FL • On-site

Full-time

Medical, Life

Re-posted 14 days ago

Job description

Are you passionate about improving data quality and readiness to unlock the full potential of AI solutions?

Do you enjoy collaborating across teams to ensure data is structured, governed, and usable for intelligent systems?

About the Business:

LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Business Services vertical, we offer a multitude of solutions focused on helping businesses of all sizes drive higher revenue growth, maximize operational efficiencies, and improve customer experience. Our solutions help our customers solve difficult problems in the areas of Anti-Money Laundering/Counter Terrorist Financing, Identity Authentication & Verification, Fraud and Credit Risk mitigation and Customer Data Management. You can learn more about LexisNexis Risk at the link below,

https://risk.lexisnexis.com

About the Team:

We are a newly formed Enterprise AI team focused on enabling agent-based solutions across the organization. We build and manage the environments, platforms, and guardrails that allow teams to create, test, and scale AI agents safely and efficiently turning experimentation into real business impact.

We're a team of curious builders and operators who are constantly exploring, learning, and applying new AI tools and approaches to solve real-world problems and improve how work gets done.

About the Role:

We are seeking an AI Data Analyst to support teams in preparing and maintaining AIready data for use in AI tools, copilots, and intelligent agents. This role focuses on data readiness, quality, metadata, and governance, helping teams understand how to structure, document, and manage their data so it can be safely and effectively used by AI systems.

The AI Data Analyst partners with data engineering, AI, and governance teams to assess data readiness, identify gaps and recommend improvements. This role does not own endtoend data pipelines and is not expected to be a deep technical expert in RAG or embeddings, but should have a solid working understanding of AIdriven data needs.

Responsibilities:

AI Data Readiness Support

  • Work with product and delivery teams to assess whether datasets and content are fit for AI use cases.
  • Help teams understand and apply AI data readiness standards, including quality, freshness, metadata, and access expectations.
  • Identify common data issues that impact AI outcomes (e.g., stale data, unclear ownership, missing metadata) and recommend remediation steps.
  • Contribute to repeatable checklists, guidance, or documentation that help teams prepare data for AI.

Data Quality & Relevance

  • Support data quality checks focused on accuracy, completeness, consistency, and timeliness for AIconsumed data.
  • Assist in monitoring and validating data freshness and relevance, escalating issues to engineering or data owners as needed.
  • Help teams improve data clarity and usability to reduce ambiguity in AI outputs.

Metadata & Semantic Enablement

  • Assist teams in improving metadata, documentation, and business descriptions so AI systems can better interpret content.
  • Support basic semantic labeling or categorization efforts that improve AI retrieval and reasoning (in coordination with engineering teams).
  • Promote good content hygiene practices (clear structure, consistent naming, wellscoped documents).

AI Data Sources & Retrieval (Support Role)

  • Support the upkeep and documentation of approved data sources used by AI solutions.
  • Help ensure data included in AI retrieval scenarios is appropriate, governed, and up to date.
  • Collaborate with AI and platform teams on data inclusion/exclusion decisions without owning technical implementation.

Governance, Lineage & Compliance Awareness

  • Help teams align AIconsumed data with enterprise governance requirements, including classification, access controls, and retention.
  • Support basic data lineage and ownership documentation for AIrelevant datasets.
  • Partner with governance and security teams by surfacing risks or gaps; does not act as final approval authority.

What This Role Does Not Own

  • Does not design or own endtoend production data pipelines.
  • Does not act as the primary technical owner for RAG frameworks, vector databases, or embedding strategies.
  • Does not make final governance or compliance decisions independently.

Requirements:

  • Proven experience in data analysis, analytics engineering, data operations, or data quality roles.
  • Good understanding of data quality principles and how poor data impacts downstream systems.
  • Experience working with structured and unstructured data (tables, files, documents, knowledge assets).
  • Proficiency in SQL and comfort investigating data issues.
  • Familiarity with data governance fundamentals (classification, access controls, ownership, retention).
  • Strong communication skills and ability to explain data concepts to nontechnical stakeholders.

Preferred Qualifications

  • Exposure to AIenabled products, copilots, or searchbased solutions.
  • Basic familiarity with AI data concepts such as semantic search, embeddings, or retrieval patterns.
  • Experience working in enterprise or regulated environments.
  • Experience contributing to standards, playbooks, or shared data practices.

What Success Looks Like

  • Teams can reliably prepare datasets that meet AI readiness expectations with less rework.
  • AI solutions benefit from more relevant, uptodate, and understandable data.
  • Clear ownership and documentation exist for data used by AI systems.
  • Strong collaboration between delivery teams, data engineering, and governance.

Working for You:

We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:

  • Medical Inpatient and Outpatient Insurance: Coverage for your healthcare needs.
  • Life Assurance Policies: Providing financial security for your loved ones.
  • Modern Family Benefits: Support for maternity, paternity, and adoption needs.
  • Long Service Award: Recognition for your dedication and loyalty.
  • Celebratory Allowance/Gifts: Marking special occasions to celebrate with you.
  • Flexible Benefits Plan : Offering you wider choice of services and products
  • Employee Assistance Program : Access support for personal and work-related challenges.
  • Flexible Working Arrangements: Balance work and personal life effectively.
  • Access to Learning and Development Resources: Empowering your professional growth.

Risk benefit statement
Learn more about the LexisNexis Risk team and how we work: https://relx.wd3.myworkdayjobs.com/RiskSolutions/page/21c296c982531000b79663f3194b0000

U.S. National Base Pay Range: $78,800 - $131,300. Geographic differentials may apply in some locations to better reflect local market rates. If performed in Ohio, the base pay range is $74,900 - $124,700. This job is eligible for an annual incentive bonus.

We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.

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