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Data Anonymization Jobs in Forney, TX (NOW HIRING)

YO AI Labs

Data Privacy Analyst - Remote

Dallas, TX · Remote

$31 - $60/hr

Data Privacy Analyst Job Type: Contractor Location: Remote Job Overview We are seeking experienced ... Conduct spot-checks of transformed datasets to verify proper redaction, masking, or anonymization ...

Mmc,-LLC-

Data Privacy Manager

Dallas, TX · On-site

$119 - $153/hr

... anonymization, and access controls, and (ii) clearly defined, auditable controls.Maintain and continuously update enterprise data flow diagrams and data inventories to map the lifecycle of personal ...

Mercor

B2B Sales Expert - AI Trainer

Dallas, TX · Remote

$35 - $50/hr

Address questions regarding data use, privacy, security, and anonymization. * Manage opportunities from initial outreach through to closing agreements. * Coordinate partner onboarding processes with ...

ASCENSUS

Senior DevOps Engineer

Dallas, TX · Hybrid

$128K - $165K/yr

Enforce data masking and PII anonymization for nonproduction environments * Validate data integrity and consistency postrefresh Observability, Reliability & Operations * Define and enforce ...

ATEM Corp

Senior Active Directory Engineer

Dallas, TX · On-site

$113K - $156K/yr

Implement and support encryption, tokenization, masking, anonymization/pseudonymization for data at rest and in transit; integrate with cloud key management systems and enforce approved cryptographic ...

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All JobsData Anonymization JobsData Anonymization Jobs in Forney, TX

Data Anonymization information

See Forney, TX salary details

$41.4K

$148.7K

$219.4K

How much do data anonymization jobs pay per year?

As of Aug 30, 2026, the average yearly pay for data anonymization in Forney, TX is $148,658.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,300.00 and $153,100.00 per year, depending on experience, location, and employer.

What is data anonymization?

Data anonymization is the process of transforming personal or sensitive data so that individuals cannot be identified, either directly or indirectly. This is typically achieved by removing or encrypting identifiers such as names, addresses, or social security numbers, and sometimes by aggregating data. The goal is to protect privacy while still allowing the data to be used for analysis or research. Data anonymization is crucial in complying with privacy regulations like GDPR and HIPAA. Properly anonymized data helps organizations minimize risk while making valuable data available for insights and decision-making.

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

To thrive in Data Anonymization, you need expertise in data privacy principles, knowledge of statistical methods, and a background in computer science, information security, or related fields. Familiarity with tools like ARX, sdcMicro, and programming languages such as Python or R, as well as understanding of regulations like GDPR, is typically required. Strong analytical thinking, attention to detail, and effective communication skills set professionals apart in this field. These competencies are crucial for ensuring sensitive information is protected while maintaining data utility for analysis and compliance.

What are some common challenges faced by professionals working in data anonymization roles?

Professionals in data anonymization often encounter challenges such as balancing data utility with privacy, ensuring compliance with evolving data protection regulations, and addressing the risk of re-identification. The work typically involves collaborating closely with data engineers, analysts, and legal teams to determine the appropriate anonymization techniques for various datasets. Staying updated on new privacy tools and methodologies is crucial, as is adapting processes to fit the unique needs of each project or organization.

What is the difference between Data Anonymization vs Data Masking?

AspectData AnonymizationData Masking
PurposeTo permanently remove or alter identifiable information to protect privacyTo temporarily hide sensitive data for testing or training
MethodData is irreversibly transformedData is reversibly masked or obscured
Use CasesData sharing, privacy compliance, anonymized analyticsTesting, development, user training
Impact on DataData becomes non-identifiable and unusable for original purposesData remains usable but obscured

While both Data Anonymization and Data Masking aim to protect sensitive information, Data Anonymization permanently alters data to prevent re-identification, making it suitable for privacy compliance and sharing. Data Masking temporarily obscures data for testing or training, allowing data usability while protecting sensitive details.

How does data anonymization work?

Data anonymization involves transforming personal data to prevent identification of individuals by removing or masking identifiable information such as names, addresses, or social security numbers. Techniques include data masking, pseudonymization, and generalization, often implemented using specialized tools and following privacy standards like GDPR or HIPAA. Data anonymization is essential for protecting privacy while enabling data analysis and sharing.

What cities near Forney, TX are hiring for Data Anonymization jobs?

Cities near Forney, TX with the most Data Anonymization job openings:

Data Anonymization jobs near you
Infographic showing various Data Anonymization job openings in Forney, TX as of June 2026, with employment types broken down into 1% As Needed, 88% Full Time, and 11% Part Time. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $148,658 per year, or $71.5 per hour.

Data Privacy Analyst - Remote

Dallas, TX • Remote

YO AI Labs
See more jobs at YO AI Labsexternal

$31 - $60/hr

Full-time

Posted 6 days ago

Job description

Data Privacy Analyst

Job Type: Contractor
Location: Remote

Job Overview

We are seeking experienced Data Privacy Analysts to support a data privacy and AI training project focused on protecting sensitive information. In this role, you will review transformed datasets and documents, identify improperly handled Personally Identifiable Information (PII), and perform detailed quality checks to ensure privacy standards are consistently maintained.

Key Responsibilities
  • Conduct spot-checks of transformed datasets to verify proper redaction, masking, or anonymization of PII.
  • Review documents and datasets for sensitive or personally identifiable information.
  • Identify missed, incorrectly handled, or improperly redacted sensitive data.
  • Evaluate data against established privacy and quality standards.
  • Document discrepancies, findings, and observations using provided tools and templates.
  • Provide clear and actionable feedback to improve data privacy and review quality.
  • Maintain confidentiality and accuracy when working with sensitive information.
Required Qualifications
  • Strong understanding of PII, data privacy, and information protection practices.
  • Experience with document review, quality assurance, eDiscovery, or compliance processes.
  • Strong attention to detail and ability to identify subtle data privacy issues.
  • Experience working with sensitive or confidential information.
  • Strong analytical and written communication skills.
  • Ability to perform repetitive and detailed spot-checks while maintaining consistent accuracy.
  • Comfortable working independently in a remote environment.
Preferred Qualifications
  • Background as a Paralegal, eDiscovery Specialist, Privacy Analyst, Information Governance Specialist, Compliance Manager, or Legal Document Review Lead.
  • Experience with legal document review, litigation support, or managed legal services.
  • Familiarity with data privacy regulations and compliance requirements.
  • Experience with contract review or legal quality assurance.
  • Experience working in high-stakes environments involving sensitive data.
Core Skills

PII | Data Privacy | Document Review | Spot Checks | eDiscovery | Quality Assurance | Data Redaction | Data Anonymization | Compliance | Attention to Detail | Sensitive Data Handling