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Data Anonymization Jobs in Minnesota (NOW HIRING)

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Data Anonymization information

What is the highest paying data job?

The highest paying data jobs often include roles such as Data Science Director, Chief Data Officer, or Data Engineering Manager, with salaries exceeding $150,000 annually depending on experience and industry. These positions typically require advanced skills in data analysis, machine learning, and leadership, along with relevant certifications or advanced degrees. Compensation varies by company size, location, and individual expertise.

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.

How to become a data privacy specialist?

To become a data privacy specialist, individuals typically need a bachelor's degree in fields like computer science, information technology, or law, along with knowledge of data protection regulations such as GDPR or CCPA. Gaining certifications like Certified Information Privacy Professional (CIPP) or Certified Information Privacy Manager (CIPM) can enhance credibility, and experience with data management, security tools, and privacy policies is valuable in this role.

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.

Why has data anonymization not taken off?

Data anonymization as a job role has not gained widespread prominence because it is often part of broader data privacy and security roles rather than a standalone position. Challenges such as balancing data utility with privacy, technical complexity, and evolving regulations have limited its standalone demand, though skills in data masking, encryption, and compliance are valuable in related fields.

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 does data anonymization do?

Data anonymization is a process used by data anonymization specialists to remove or obscure personally identifiable information from datasets, ensuring individual privacy while maintaining data utility. It helps organizations comply with data protection regulations and enables secure data sharing for analysis or research. Techniques include masking, pseudonymization, and generalization, often performed using specialized tools and requiring attention to data security standards.

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 Minnesota? For Data Anonymization jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Data Anonymization jobs in Minnesota look for? The top searched job categories for Data Anonymization jobs in Minnesota are:
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Data Anonymization jobs near you
Full Stack Developer (.Net)

Full Stack Developer (.Net)

DivIHN Integration Inc

Saint Paul, MN • On-site

$75 - $80/hr

Contractor

Posted 24 days ago

Job description

DivIHN (pronounced “divine”) is a CMMI ML3-certified Technology and Talent solutions firm. Driven by a unique Purpose, Culture, and Value Delivery Model, we enable meaningful connections between talented professionals and forward-thinking organizations. Since our formation in 2002, organizations across commercial and public sectors have been trusting us to help build their teams with exceptional temporary and permanent talent.

Visit us at https://divihn.com/find-a-job/ to learn more and view our open positions.

 
Please apply or call one of us to learn more

For further inquiries about this opportunity, please contact one of our Talent Specialists, Lavanya at (224) 369 0873 , (or) Ragu at (224) 704 1713 .

Title: Full Stack Developer (.Net) 
Duration: 12 Months (with possible extension)
Location: St. Paul, MN

Only W2 candidates are eligible for this position. Third-party or C2C candidates will not be considered.

Job Description:
  • We are seeking a Full‑Stack Developer with strong experience in backend development using C#/.NET and frontend development using Angular, along with solid data engineering skills.
  • This role will support the development and enhancement of a data platform used for ingesting, managing, and analyzing large‑scale imaging and electrophysiology procedural datasets.
  • The ideal candidate is hands‑on across the full stack and comfortable working with data pipelines, APIs, and scalable enterprise systems.
Key Responsibilities
  • Design and develop full stack web applications for data ingestion, management, visualization, and labeling
  • Build and maintain backend services and REST APIs to support data workflows
  • Design and implement data pipelines for ingesting, transforming, and storing large datasets
  • Integrate data from multiple external systems and sources
  • Support longitudinal data tracking and versioning across datasets
  • Collaborate closely with data scientists, R&D engineers, and domain experts
  • Ensure performance, reliability, and maintainability of the platform
  • Follow best practices for data security, privacy, and compliance
Required Skills & Qualifications
Full Stack Development
  • Strong experience in full stack development (frontend and backend)
  • Strong experience with C# and .NET (.NET Core / .NET Framework)
  • Frontend: Strong experience with Angular (TypeScript, HTML, CSS)
  • Experience with RESTful APIs and microservices architecture
Data Engineering
  • Experience designing and building data pipelines (ETL/ELT)
  • Strong data modeling skills
  • Experience with PostgreSQL and NoSQL databases
  • Familiarity with cloud based data storage and compute (Azure preferred)
Preferred / Nice to Have Skills
  • Experience working with large imaging and time series datasets
  • Exposure to healthcare, clinical, or regulated data environments
  • Familiarity with data anonymization or pseudonymization techniques
  • Experience supporting ML/AI data preparation workflows
  • DevOps experience (CI/CD pipelines, containerization)
Deliverables & Expectations
  • Scalable and reliable data ingestion and management capabilities
  • Well documented, production quality code
  • Improved support for longitudinal and multi source data workflows
  • Close collaboration with internal teams to meet project timelines

About us:
DivIHN, the 'IT Asset Performance Services' organization, provides Professional Consulting, Custom Projects, and Professional Resource Augmentation services to clients in the Mid-West and beyond. The strategic characteristics of the organization are Standardization, Specialization, and Collaboration.

DivIHN is an equal opportunity employer. DivIHN does not and shall not discriminate against any employee or qualified applicant on the basis of race, color, religion (creed), gender, gender expression, age, national origin (ancestry), disability, marital status, sexual orientation, or military status.