How to Build a Successful Career in Privacy

What Does It Take to Build a Career in Privacy?

A successful career in privacy requires more than knowing the law. It takes judgment, curiosity, business fluency, strong cross-functional relationships, and the ability to turn incomplete facts into decisions an organization can explain and defend.

Judy Titera learned that early when she raised her hand for a project outside her comfort zone. That assignment became a 25-year career building privacy programs through changing laws, technologies, and public expectations.

In this recap of a Privacy Collective live Q&A, Titera shares seven lessons for people entering or advancing in privacy, from taking stretch assignments and finding mentors to preparing for AI-related risk and using technology to support consistent incident response.

How Privacy Work Has Changed

Titera entered privacy in 1998, just before several major US privacy requirements began to reshape regulated industries. The Gramm-Leach-Bliley Act became law in 1999, and HHS proposed the HIPAA Privacy Rule later that year. California enacted its breach notification law in 2002, effective in 2003. Federal health care breach notification requirements followed under HITECH in 2009, with the HIPAA Omnibus Rule published in 2013.

As a result, the profession now operates across law, risk, security, data governance, product, communications, and AI. Privacy teams may need to assess an event across jurisdictions, determine whether notification is required, coordinate action, and preserve the reasoning behind the decision.

The operating model has changed, but the core responsibility has not: understand how data use can affect people, make a well-supported decision, and be prepared to explain it.

Seven Lessons for Building a Privacy Career

1. Raise Your Hand Before You Feel Ready

Titera did not set out to work in privacy. She was a paralegal at an insurance company when a new project needed support. She volunteered and went on to help implement the company’s GLBA and HIPAA programs.

Her advice is straightforward: volunteer for unfamiliar or uncomfortable work and use it to learn. A stretch assignment may not look like a career move at first, but it can reveal a field, a skill, or a business problem you would not otherwise encounter.

Early-career professionals can contribute to a data inventory, incident tabletop exercise, policy review, privacy impact assessment, or AI use-case assessment. Experienced practitioners can join cross-functional programs where answers are still taking shape. Both approaches build knowledge and show how the organization makes decisions under pressure.

2. Learn the Business and Build a Cross-Functional Network

Titera quickly learned that privacy is a team effort. She expected to focus on policies and notices, but the job quickly became a close partnership with information security.

That partnership now extends to legal, compliance, IT, product, human resources, communications, and business leaders. Each group sees a different part of an incident or data-use decision. A mature program gives those perspectives a shared operating model, turning them into complete, consistent information rather than disconnected emails, spreadsheets, and assumptions.

Knowing the business is equally important. Privacy professionals need to understand not only which requirements apply, but also how data moves, who owns the process, how the organization creates value, and where a decision can create harm. NIST’s Privacy Framework emphasizes tailoring privacy outcomes to an organization’s mission, operating environment, stakeholder expectations, and risk tolerance.

3. Develop Judgment, Not Just Legal Knowledge

Privacy is full of gray areas. Laws evolve, guidance may not map neatly to a specific fact pattern, and business teams often need an answer before every uncertainty is resolved. Critical thinking and curiosity matter because the role requires more than reading a rule and checking a box.

Strong practitioners ask disciplined questions:

• What happened, and which facts are still missing?
• Whose data is involved, and what is the likely impact on people?
• Which jurisdictions, contracts, and internal policies apply?
• What assumptions shape the assessment?
• What rationale supports the final decision?

The goal is a conclusion the organization can explain and defend, not certainty manufactured from incomplete information.

Titera also encourages practitioners to read the law itself. Certifications, webinars, and summaries can accelerate learning, but primary sources reveal definitions, exceptions, and regulatory intent that summaries may compress.

4. Treat Learning and Networking as Part of the Job

Privacy is not a field you learn once. New uses of data, new regulatory expectations, and new technologies continually change the questions practitioners must answer. Build a repeatable learning habit: follow developments that affect your organization, attend focused sessions, read primary materials, and compare approaches with trusted peers.

Networking makes that learning practical. A peer conversation can reveal how another team frames a new requirement or structures an escalation process. The purpose is not to exchange confidential information. It is to understand how thoughtful practitioners approach the same operational problem.

The profession also continues to expand into adjacent disciplines. According to the IAPP Privacy Governance Report 2024, 55% of surveyed privacy professionals worked in functions with AI governance responsibilities, 58% had taken on data governance and data ethics, and 32% covered cybersecurity regulatory compliance. These findings show how broadly privacy responsibilities can extend, but they don’t guarantee job-market growth.

5. Build Two Kinds of Mentorship

Titera recommends maintaining two mentoring relationships. The first is a professional mentor who can help you understand the field, evaluate opportunities, and make career decisions. The second is a trusted adviser outside your immediate reporting line who can help you think through difficult situations and regain perspective.

To make mentorship useful:

• Ask directly and give the person room to decline if they do not have capacity.
• Choose someone whose judgment you admire and whose company you enjoy.
• Explain what you hope to learn and what kind of relationship you are seeking.
• Prepare for each conversation, follow through, and respect the mentor’s time.
• Reassess when the relationship no longer serves either person’s needs.

Mentorship is not limited to people starting out. Senior leaders also benefit from a confidential place to test their reasoning, challenge assumptions, and stay grounded.

6. Build Technical Fluency Before an Incident

AI and connected systems can change what data an organization uses, how quickly it moves, who can access it, and how an incident affects people. Privacy professionals don’t need to become engineers, but they do need enough technical fluency to investigate these conditions before a high-impact event forces the organization to improvise.

Start with operational questions: What data enters the system? Where did it come from? What output does the system produce? Who can access the data and output? How long are they retained? Which third parties are involved? What testing and monitoring exist? When must a person review or override the system?

The NIST AI Risk Management Framework offers a voluntary structure for managing AI risks to individuals, organizations, and society. Its generative AI profile identifies risks that are unique to or intensified by generative AI and proposes actions organizations can adapt to their goals and priorities.

7. Minimize Data and Document Your Reasoning

Good privacy judgment begins before an incident. Collecting and retaining less personal information can reduce exposure to unauthorized access or use. It also forces the organization to clarify why it needs the data, who should access it, and when it should be deleted.

NIST’s privacy considerations for identity proofing state that data minimization reduces the amount of personal information vulnerable to unauthorized access or use. The principle applies more broadly: information that is not collected or retained cannot be exposed later.

When an incident does occur, defensibility depends on the process used to reach the decision. Teams need complete intake, a consistent assessment, clear regulatory mapping, documented assumptions, and an auditable history of actions. Privacy professionals who can create that record give the organization more than an answer; they provide proof of diligence.

For a career in privacy, the practical lesson is simple: do not stop at the conclusion. Preserve the facts, requirements, and reasoning that made the conclusion supportable.

How Technology Supports Accountable Privacy Decisions

As privacy responsibilities expand, individual judgment must work inside a repeatable process. Spreadsheets and email can capture pieces of an assessment, but they make it harder to maintain consistent intake, keep regulatory logic current, and preserve a complete decision history across teams.

Titera saw that gap when her team was managing incidents and changing laws in spreadsheets. A RadarFirst demo showed how purpose-built technology could give the team a more structured way to work.

RadarFirst connects structured intake, guided risk assessment, regulatory intelligence, decision support, and documentation across privacy and AI incidents. The platform helps teams apply consistent logic and preserve supporting rationale while the organization retains control of the final decision.

That distinction matters. Technology should not replace accountable human judgment. It should help privacy professionals reach decisions faster, with greater continuity and proof of diligence.

Privacy Careers Span Legal, Operational, and Technical Work

A career in privacy no longer maps to a single title or background. Opportunities span privacy operations, incident response, data governance, product counseling, engineering, cybersecurity compliance, and AI governance. Each path needs people who can investigate facts, communicate clearly, and make risk-informed decisions.

A law degree is not the only route into the field. Legal knowledge matters, but so do transferable skills from security, compliance, product, data, engineering, communications, and operations. The strongest path is the one that pairs your existing experience with practical privacy work and a clear understanding of the business.

Choose Your Next Practical Step

You do not need a perfect career plan to move forward. Choose one practical step that builds evidence of your ability: volunteer for an unfamiliar project, read the primary rule behind a current requirement, map how data moves through a business process, join an incident exercise, or ask a trusted practitioner for focused guidance.

A successful privacy career grows through informed decisions and follow-through. The same is true of a mature privacy program.

See How Privacy Teams Operationalize Good Judgment

Privacy professionals need more than regulatory knowledge. They need a repeatable way to capture facts, assess risk, apply current requirements, and preserve the rationale behind a decision. See how RadarFirst helps teams standardize privacy and AI incident response while keeping accountable people in control of the final decision.

Explore the RadarFirst platform

Sources

• RadarFirst platform
• NIST Using Privacy Framework 1.1
• NIST AI Risk Management Framework
• NIST Privacy Considerations for Identity Proofing
• IAPP Privacy Governance Report 2024
• California Department of Justice Privacy Legislation Enacted in 2002
• HHS Breach Notification Regulation History
• FTC How to Comply with the Privacy of Consumer Financial Information Rule
• HHS HIPAA Privacy Rule History