... anonymization, and privacy-preserving capabilities to meet compliance requirements. • Collaborate with Analytics, Risk, Credit Policy, and Technology teams to align data solutions with business ...
... anonymization, and privacy-preserving capabilities to meet compliance requirements. • Collaborate with Analytics, Risk, Credit Policy, and Technology teams to align data solutions with business ...
Implement data quality, metadata management, anonymization, and privacy-preserving capabilities to meet compliance requirements. * Collaborate with Analytics, Risk, Credit Policy, and Technology ...
Implement data quality, metadata management, anonymization, and privacy-preserving capabilities to meet compliance requirements. * Collaborate with Analytics, Risk, Credit Policy, and Technology ...
Implement data quality, metadata management, anonymization, and privacy-preserving capabilities to meet compliance requirements. * Collaborate with Analytics, Risk, Credit Policy, and Technology ...
Implement data quality, metadata management, anonymization, and privacy-preserving capabilities to meet compliance requirements. * Collaborate with Analytics, Risk, Credit Policy, and Technology ...
Cribl Engineer
Alexandria, VA · On-site
$125K - $140K/yr
Collaborate with governance teams to align on data retention, anonymization, and privacy requirements. * Support continuous improvement by analyzing ingestion efficiency, performance benchmarks, and ...
Cribl Engineer
Alexandria, VA · On-site
$125K - $140K/yr
Collaborate with governance teams to align on data retention, anonymization, and privacy requirements. * Support continuous improvement by analyzing ingestion efficiency, performance benchmarks, and ...
Data Anonymization information
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 is the difference between Data Anonymization vs Data Masking?
| Aspect | Data Anonymization | Data Masking |
|---|---|---|
| Purpose | To permanently remove or alter identifiable information to protect privacy | To temporarily hide sensitive data for testing or training |
| Method | Data is irreversibly transformed | Data is reversibly masked or obscured |
| Use Cases | Data sharing, privacy compliance, anonymized analytics | Testing, development, user training |
| Impact on Data | Data becomes non-identifiable and unusable for original purposes | Data 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.
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 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 popular job titles related to Data Anonymization jobs in Virginia? For Data Anonymization jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Data Anonymization jobs in Virginia look for? The top searched job categories for Data Anonymization jobs in Virginia are:
What cities in Virginia are hiring for Data Anonymization jobs? Cities in Virginia with the most Data Anonymization job openings:
Job description
Job Summary:
Freddie Mac is an organization dedicated to making home possible for families across the country. The Director of Consumer Data Strategy will oversee the development and execution of data initiatives to support Single-Family Acquisitions analytics and reporting, acting as a bridge between business, technology, and data governance teams.
Responsibilities:
• Define and execute a comprehensive data strategy for Credit Risk Management and Single-Family analytics, ensuring alignment with enterprise priorities.
• Develop and manage the roadmap for data modernization, including cloud migration, data lake/CDW adoption, and the decommissioning of legacy data pipelines.
• Advocate for the adoption of industry standards (e.g., MISMO) to enhance data consistency, interoperability, and regulatory compliance.
• Innovate and develop reports, tools, and processes to meet emerging data requirements for mission analytics and reporting.
• Strategically develop and oversee Tableau dashboards to support robust reporting, analysis, and critical business processes.
• Manage mission-critical data management workflows that enable analytics and reporting capabilities, including the preparation of securities data.
• Organize and lead quarterly quality control meetings to ensure comprehensive data accuracy and uniformity in FHFA reporting.
• Collaborate with audit teams to promptly address and resolve any identified audit findings.
• Provide detailed requirements for Affordable Housing Goals and Duty to Serve reporting applications, and conduct user acceptance testing to verify functionality.
• Partner with the Single-Family Analytics Center of Excellence (SF Analytics COE) to support the data domain and uphold best practices.
• Lead the preparation and processing of Home Mortgage Disclosure Act (HMDA) data for analytics and reporting applications.
• Analyze FHFA reference files and prepare data for dissemination to other teams, such as RDS.
• Design and deliver data products that offer a comprehensive view of the loan, borrower, and collateral lifecycle.
• Oversee the ingestion, transformation, and quality management of high-value datasets (e.g., acquisition, appraisal, servicing, performance data).
• Implement data quality, metadata management, anonymization, and privacy-preserving capabilities to meet compliance requirements.
• Collaborate with Analytics, Risk, Credit Policy, and Technology teams to align data solutions with business needs.
• Serve as a subject matter expert for MISMO adoption and data standards across origination, collateral, and loan lifecycle.
Qualifications:
Required:
• Bachelor’s degree in Computer Science preferred or equivalent work experience
• 12+ years of related experience and 4+ years of management experience
• Experience in credit risk analytics, loan origination/acquisition data.
• Familiarity with regulatory reporting requirements in the mortgage industry.
• Hands-on experience with modern data tools (e.g., Python, SQL, Spark, Informatica, Collibra).
• Experience driving large-scale enterprise data initiatives with measurable outcomes.
• Prior engagement with industry bodies or vendor standardization efforts.
Company:
Freddie Mac is a public government-sponsored enterprise that provides mortgage capital to lenders. Founded in 1970, the company is headquartered in Mclean, USA, with a team of 5001-10000 employees. The company is currently Late Stage.
Freddie Mac is an organization dedicated to making home possible for families across the country. The Director of Consumer Data Strategy will oversee the development and execution of data initiatives to support Single-Family Acquisitions analytics and reporting, acting as a bridge between business, technology, and data governance teams.
Responsibilities:
• Define and execute a comprehensive data strategy for Credit Risk Management and Single-Family analytics, ensuring alignment with enterprise priorities.
• Develop and manage the roadmap for data modernization, including cloud migration, data lake/CDW adoption, and the decommissioning of legacy data pipelines.
• Advocate for the adoption of industry standards (e.g., MISMO) to enhance data consistency, interoperability, and regulatory compliance.
• Innovate and develop reports, tools, and processes to meet emerging data requirements for mission analytics and reporting.
• Strategically develop and oversee Tableau dashboards to support robust reporting, analysis, and critical business processes.
• Manage mission-critical data management workflows that enable analytics and reporting capabilities, including the preparation of securities data.
• Organize and lead quarterly quality control meetings to ensure comprehensive data accuracy and uniformity in FHFA reporting.
• Collaborate with audit teams to promptly address and resolve any identified audit findings.
• Provide detailed requirements for Affordable Housing Goals and Duty to Serve reporting applications, and conduct user acceptance testing to verify functionality.
• Partner with the Single-Family Analytics Center of Excellence (SF Analytics COE) to support the data domain and uphold best practices.
• Lead the preparation and processing of Home Mortgage Disclosure Act (HMDA) data for analytics and reporting applications.
• Analyze FHFA reference files and prepare data for dissemination to other teams, such as RDS.
• Design and deliver data products that offer a comprehensive view of the loan, borrower, and collateral lifecycle.
• Oversee the ingestion, transformation, and quality management of high-value datasets (e.g., acquisition, appraisal, servicing, performance data).
• Implement data quality, metadata management, anonymization, and privacy-preserving capabilities to meet compliance requirements.
• Collaborate with Analytics, Risk, Credit Policy, and Technology teams to align data solutions with business needs.
• Serve as a subject matter expert for MISMO adoption and data standards across origination, collateral, and loan lifecycle.
Qualifications:
Required:
• Bachelor’s degree in Computer Science preferred or equivalent work experience
• 12+ years of related experience and 4+ years of management experience
• Experience in credit risk analytics, loan origination/acquisition data.
• Familiarity with regulatory reporting requirements in the mortgage industry.
• Hands-on experience with modern data tools (e.g., Python, SQL, Spark, Informatica, Collibra).
• Experience driving large-scale enterprise data initiatives with measurable outcomes.
• Prior engagement with industry bodies or vendor standardization efforts.
Company:
Freddie Mac is a public government-sponsored enterprise that provides mortgage capital to lenders. Founded in 1970, the company is headquartered in Mclean, USA, with a team of 5001-10000 employees. The company is currently Late Stage.
About Freddie Mac
Sourced by ZipRecruiter
Today, Freddie Mac makes home possible for one in four home borrowers and is one of the largest sources of financing for multifamily housing. Join our smart, creative and dedicated team and you'll do important work for the housing finance system and make a difference in the lives of others.
Industry
Finance and insurance
Company size
5,001 - 10,000 Employees
Headquarters location
McLean, VA, US
Year founded
1970