Description -

Job Summary

- Role Purpose

• This role will design and implement scalable AI-ready data privacy architecture across enterprise data environments applications and AI-enabled workflows.

• The Principal Data Privacy Architect will serve as a hands-on subject matter expert responsible for embedding privacy-by-design consent enforcement data sovereignty data loss prevention and compliance controls into large complex global data environments.

• The architect will partner closely with Data Engineering Cybersecurity Legal Privacy AI Governance Product and Enterprise Architecture teams to ensure customer employee partner and sensitive enterprise data is accessed processed shared retained and protected in a compliant secure and trustworthy manner.

- Why This Role Matters

• Architect for Trust & Scale: Build reusable privacy architecture patterns that enable secure compliant and scalable data usage across platforms products and regions.

• Enable Responsible AI: Design privacy guardrails for AI agents generative AI RAG pipelines model inputs and outputs embeddings vector stores and automated data workflows.

• Reduce Risk While Enabling Innovation: Translate privacy consent regulatory and data sovereignty obligations into practical engineering controls that accelerate business outcomes.

Responsibilities

- Think Customer First

• Embed customer trust transparency and privacy-by-design principles into enterprise data platforms and customer-facing applications.

• Design consent-aware data access and usage patterns across analytics personalization marketing product telemetry support and AI use cases.

• Ensure customer data is collected processed shared retained and deleted according to approved purposes consent preferences and regulatory obligations.

- Innovate for Growth

• Architect reusable privacy engineering components including APIs SDKs reference architectures automation patterns and policy-as-code controls.

• Design privacy controls for AI agents and AI-enabled workflows that access process summarize or publish sensitive data.

• Build technical patterns for data minimization anonymization pseudonymization tokenization encryption masking and secure data sharing.

- Act with Integrity

• Partner with Legal Privacy Cybersecurity and Compliance teams to translate global privacy regulations and internal policies into enforceable technical controls.

• Support compliance with GDPR CCPA/CPRA LGPD PIPL India DPDP Act data sovereignty mandates cross-border transfer requirements and regional data residency obligations.

• Define auditable controls for consent enforcement access monitoring retention deletion lineage and compliance evidence collection.

- Build for the Future

• Establish privacy architecture patterns across data warehouses lakehouses metadata platforms customer data platforms AI/ML environments vector databases and cloud platforms.

• Integrate sensitive data discovery classification lineage DLP DSPM IAM KMS and monitoring capabilities into the enterprise data ecosystem.

• Advance automated compliance monitoring privacy control validation and risk detection across the data lifecycle.

- Work as One Team

• Collaborate with Data Engineering Product AI Governance Cybersecurity Legal Privacy and Enterprise Architecture teams to embed privacy controls into delivery workflows.

• Provide hands-on architecture guidance for high-risk data initiatives AI programs customer data products and platform modernization efforts.

• Mentor engineers architects data scientists and product teams on privacy engineering best practices.

Strategic & Technical Focus Areas

• AI-Ready Privacy Architecture: Privacy controls for AI agents generative AI RAG pipelines model inputs and outputs embeddings vector stores and automated data workflows.

• Consent & Purpose-Based Usage: Consent propagation purpose limitation consent revocation customer preference enforcement and downstream data usage controls.

• Data Loss Prevention & Sensitive Data Protection: DLP integration sensitive data classification risky sharing detection exfiltration prevention and AI prompt/output inspection.

• Data Sovereignty & Compliance Engineering: Regional data residency cross-border transfer controls localization requirements encryption key residency and audit evidence automation.

• Reusable Privacy Frameworks: Standardized architecture patterns for encryption masking tokenization anonymization retention deletion access control and monitoring.

Education & Experience & Skills

- Education & Experience

• Bachelors or masters degree in Computer Science Engineering Information Systems Cybersecurity Data Engineering or related field.

• 10 years of progressive experience in data privacy data protection cybersecurity data architecture or enterprise data platforms.

• Proven experience architecting privacy and data protection solutions in large complex global environments.

• Hands-on experience implementing privacy-by-design consent management data sovereignty DLP and sensitive data protection controls.

- Technical Expertise

• Strong understanding of global privacy regulations and frameworks including GDPR CCPA/CPRA LGPD PIPL India DPDP Act NIST ISO 27001 and related privacy/security standards.

• Experience with cloud platforms such as AWS Azure or GCP and enterprise data platforms including data warehouses lakehouses data catalogs metadata platforms and big data environments.

• Working knowledge of privacy and data protection technologies such as BigID OneTrust Securiti Collibra Informatica Microsoft Purview AWS Macie Google Cloud DLP Azure Information Protection DLP DSPM CASB IAM and KMS capabilities.

• Strong technical skills in Python Java SQL APIs Spark data pipelines infrastructure-as-code and policy-as-code.

• Experience with AI/ML generative AI AI agents RAG architectures vector databases feature stores model governance or AI-enabled data products.

- Leadership & Business Skills

• Ability to translate legal privacy compliance and business requirements into scalable technical architecture.

• Strong communication and influencing skills with engineers architects legal teams privacy teams product leaders and senior executives.

• Demonstrated ability to balance customer trust regulatory compliance engineering practicality and business agility.

- Preferred Qualifications

• Certifications such as CIPP/E CIPP/US CIPM CIPT CISSP CCSP CDPSE or equivalent.

• Experience building consent management platforms privacy preference centers data subject rights automation or customer data governance capabilities.

• Experience implementing purpose-based access control attribute-based access control zero-trust data architecture or data-centric security models.

• Active industry participation publications or memberships related to privacy engineering AI governance cybersecurity or customer trust.

- Cross-Org Skills

• Effective Communication

• Results Orientation

• Learning Agility

• Digital Fluency

• Customer Centricity

Salary

The pay range for this role is 154400.00 - 227750.00 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United
States of America candidates only). Pay varies by work location job-related
knowledge skills and experience.

Benefits:

HP offers a comprehensive benefits package for this position including:

* Health insurance
* Dental insurance
* Vision insurance
* Long term/short term disability insurance
* Employee assistance program
* Flexible spending account
* Life insurance
* Generous time off policies including;
* 4-12 weeks fully paid parental leave based on tenure
* 11 paid holidays
* Additional flexible paid vacation and sick leave (US benefits overview
compensation and benefits information is accurate as of the date of this
posting. The Company reserves the right to modify this information at any time
with or without notice subject to applicable law.

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Equal Opportunity Employer (EEO) -

HP Inc. provides equal employment opportunity to all employees and prospective employees without regard to race color religion sex national origin ancestry citizenship sexual orientation age disability or status as a protected veteran marital status familial status physical or mental disability medical condition pregnancy genetic predisposition or carrier status uniformed service status political affiliation or any other characteristic protected by applicable national federal state and local law(s).

Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence.

For more information review HPsEEO Policy or read about your rights as an applicant under the law here: Know Your Rights: Workplace Discrimination is Illegal